CN112084688B - Cathode life prediction method - Google Patents
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Abstract
The application relates to the technical field of electron beam selective melting additive manufacturing, and discloses a cathode life prediction method. According to the cathode life prediction method, printing tests are carried out on the EBSM printing equipment, the variation relation between the poisoning depth of the cathode and printing time under different air pressure environments is obtained, and therefore a poisoning depth model of the cathode is built. In the actual use process of the EBSM printing device, the poisoning depth of the cathode in the printing process is obtained by monitoring the printing time, the air pressure in the electron gun and the air pressure in the forming cavity and combining the poisoning depth model of the cathode obtained through the test. And obtaining the residual service life of the cathode through the poisoning depth to complete the service life prediction of the cathode. The cathode life prediction method provided by the application is based on the poisoning failure mechanism of the cathode to realize the prediction of the residual life of the cathode in the actual EBSM printing process, and the prediction effect is more accurate and reliable.
Description
Technical Field
The application relates to the technical field of electron beam selective melting additive manufacturing, in particular to a cathode life prediction method.
Background
EBSM (Electronic Beam Selective Melting, electron beam selective melting) additive manufacturing technology is one of the powder-laid additive manufacturing technologies that heats powder metal using an electron beam as an energy source, causes it to melt rapidly, solidify, and print-forms layer-by-layer to manufacture parts. Since the electron beam energy density is much higher than the laser beam energy density, it is of great advantage when applied to many highly reflective, high melting point materials. However, the cathode or filament is a core part of the EBSM apparatus, so the service life of the cathode or filament almost determines the maintenance period of the EBSM apparatus, and the service life prediction of the cathode or filament is particularly critical because the cathode or filament itself is expensive. In the prior art, the life prediction precision of the cathode is poor.
Disclosure of Invention
Based on this, it is necessary to provide a cathode lifetime prediction method for solving the problem of poor lifetime prediction accuracy for the cathode in the prior art.
The cathode life prediction method is applied to an EBSM printing device, wherein the EBSM printing device comprises an electron gun and a forming cavity, the electron gun comprises a cathode, the cathode life prediction method comprises the steps of performing an EBSM printing test on the EBSM printing device, and establishing a poisoning depth model of the cathode of the electron gun in the EBSM printing process; at least one acquisition point is respectively arranged in the electron gun and the forming cavity, and when the EBSM printing operation is actually performed, the actual printing time, the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity are acquired and recorded in real time; the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity are combined, and the air pressure value of the emitting surface of the cathode is obtained in a finite element simulation mode; and predicting the residual life of the cathode according to the air pressure value of the emission surface and the poisoning depth model.
According to the cathode life prediction method, the printing test is carried out on the EBSM printing equipment, the variation relation between the poisoning depth of the cathode and the printing time under different air pressure environments is obtained, and the poisoning depth model of the cathode is built. In the actual use process of the EBSM printing device, the poisoning depth model of the cathode, which is obtained through a combination test, is obtained by monitoring the printing time, the air pressure in the electron gun and the air pressure in the forming cavity so as to obtain the poisoning depth of the cathode in the printing process, and the residual service life of the cathode is obtained through the poisoning depth so as to complete the service life prediction of the cathode. The technical scheme of the application is to predict the residual life of the cathode in the actual EBSM printing process based on the poisoning failure mechanism of the cathode, and the prediction effect is more accurate and reliable.
In one embodiment, the establishing the poisoning depth model of the cathode of the electron gun in the EBSM printing process includes fitting a life distribution model of the cathode according to the replacement time of the cathode of the electron gun in the historical statistics; selecting a plurality of preset observation points according to the life distribution model to respectively perform an EBSM printing test, and recording the test printing time, the test air pressure value of the electron gun and the test air pressure value of the forming cavity in real time in the test process; stopping printing test when reaching each preset observation point in the test process of each preset observation point, and obtaining the poisoning depth of the cathode at each preset observation point; for different preset air pressure values at each preset observation point, respectively constructing a change relation between the poisoning depth of the cathode emission surface and the printing time under different preset air pressure values in a curve fitting mode to be used as a poisoning depth model of the cathode; wherein the number of the poisoning depth models is not less than three.
In one embodiment, the selecting a plurality of preset observation points according to the lifetime distribution model includes taking lifetime estimation of the cathode at a preset confidence level in the lifetime distribution model as a preset observation point x R The method comprises the steps of carrying out a first treatment on the surface of the At 0 to the preset observation point x R Selecting N preset observation points x 1 、x 2 ...x N And recording the preset observation point x 1 、x 2 ...x N 、x R The method comprises the steps of carrying out a first treatment on the surface of the Wherein N is greater than or equal to 4 and 0<x 1 <x 2 <x N <x R 。
In one embodiment, the lifetime distribution model is a lognormal distribution:
wherein x is the estimated lifetime of the cathode, f (x) is the distribution function of the estimated lifetime of the cathode, μ is the mean value of the estimated lifetime of the cathode, and σ is the standard deviation of the estimated lifetime of the cathode.
In one embodiment, the relationship between the poisoning depth of the cathode emission surface and the printing time at the preset air pressure value is:
d＝Aexp(-B/t 2 )；
wherein d is the poisoning depth of the cathode, t is the printing time, and A and B are constants related to the cathode material, the material processed in the EBSM printing process and the preset air pressure value.
In one embodiment, the electron gun comprises a first vacuum pump, the forming cavity comprises a second vacuum pump, the obtaining of the air pressure value of the emitting surface of the cathode through a finite element simulation mode comprises taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure of the position of the first vacuum pump as an outlet, obtaining a first outlet pressure function or a first speed function of the electron gun, and applying the first outlet pressure function or the first speed function to the first vacuum pump; taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure at the position of the second vacuum pump as an outlet, acquiring a second outlet pressure function or a second speed function of the forming cavity, and applying the second outlet pressure function or the second speed function to the second vacuum pump; establishing a finite element model of a flow field in an actual printing process according to the first outlet pressure function and the second outlet pressure function or the first speed function and the second speed function; and extracting an air pressure average value in a preset area near the emitting surface of the cathode, and taking the air pressure average value as the air pressure value of the emitting surface of the cathode.
In one embodiment, when the finite element model of the flow field in the actual printing process is established, the method further includes correcting the finite element model by using the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity as correction points, so as to obtain an accurate finite element model of the flow field.
In one embodiment, the predicting the residual life of the cathode according to the air pressure value of the emission surface and the poisoning depth model includes interpolating an actual poisoning depth model of the cathode at the air pressure value of the emission surface by not less than three poisoning depth models based on the air pressure value of the emission surface; acquiring a service life value of the cathode under a preset confidence coefficient according to the actual poisoning depth model and the actual printing time; the remaining lifetime of the cathode is the difference between the lifetime value and the actual printing time.
In one embodiment, the interpolating the actual poisoning depth model of the cathode at the barometric pressure value of the emission surface by the poisoning depth models of not less than three includes fitting a relation between the parameter a and the parameter B and the barometric pressure value by the poisoning depth models of not less than three; and acquiring the values of the parameter A and the parameter B under the air pressure value of the emission surface according to the relation between the parameter A and the parameter B and the air pressure value respectively so as to establish an actual poisoning depth model of the cathode under the air pressure value of the emission surface.
In one embodiment, the relationship between the parameter a and the air pressure value is:
A＝C*t 2 *p*exp(-1/p)；
the relation between the parameter B and the air pressure value is as follows:
B＝-t 2 /p；
wherein t is printing time, p is an air pressure value, and C is a constant related to the air pressure value p.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments or the conventional techniques of the present application, the drawings required for the descriptions of the embodiments or the conventional techniques will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.
FIG. 1 is a flow chart of a method for predicting the lifetime of a cathode according to an embodiment of the application;
fig. 2 is an internal structural view of an EBSM printing apparatus according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for modeling the poisoning depth of a cathode according to an embodiment of the present application;
FIG. 4 is a flow chart of a method for selecting a preset observation point according to an embodiment of the application;
FIG. 5 is a flow chart of a method for acquiring an emission surface air pressure value through finite element simulation according to an embodiment of the present application;
FIG. 6 is a flow chart of a method of modeling finite element of a flow field according to one embodiment of the present application;
FIG. 7 is a flow chart of a method for predicting the residual life of a cathode according to one embodiment of the application.
Detailed Description
In order that the application may be readily understood, a more complete description of the application will be rendered by reference to the appended drawings. The drawings illustrate preferred embodiments of the application. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," "upper," "lower," "front," "rear," "circumferential," and the like as used herein are based on the orientation or positional relationship shown in the drawings and are merely for convenience of description and to simplify the description, rather than to indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus are not to be construed as limiting the application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
EBSM (Electronic Beam Selective Melting, electron beam selective melting) technology is one of the additive manufacturing technologies of powder spreading. EBSM mainly uses electron beams as energy sources to heat powder metal, rapidly melt it, solidify it, and print it layer by layer to make parts. Since the electron beam must propagate in vacuum, the cathode of the electron gun is directly exposed to the heated metal material. Generally, vacuum pumps of different magnitudes are used in the electron gun and the forming chamber to minimize the probability of contamination or poisoning of the cathode or filament. However, in practical use, the influence of gases such as metal vapor, oxygen, nitrogen and the like on the service life of the cathode or the filament is far greater than the influence caused by volatilization of materials of the cathode or the filament. The effect of the gas on the cathode or filament is mainly poisoning or direct evaporation. Metal vapors and residual gases generated during EBSM processing can cause cathode poisoning and thereby accelerate cathode failure. Therefore, in the present application, it is proposed to monitor the gas pressure inside the electron gun and the gas pressure in the forming chamber to obtain the poisoning depth of the cathode, and further predict the residual life value of the cathode through the poisoning depth of the cathode.
Fig. 1 is a flowchart of a method for predicting a cathode lifetime according to an embodiment of the application, wherein the method for predicting a cathode lifetime includes the following steps S100 to S400.
S100: and carrying out an EBSM printing test on the EBSM printing equipment, and establishing a poisoning depth model of the cathode of the electron gun in the EBSM printing process.
S200: at least one acquisition point is respectively arranged in the electron gun and the forming cavity, and when the EBSM printing operation is actually performed, the actual printing time, the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity are acquired and recorded in real time.
S300: and acquiring the air pressure value of the emitting surface of the cathode in a finite element simulation mode by combining the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity.
S400: and predicting the residual life of the cathode according to the air pressure value of the emission surface and the poisoning depth model.
Fig. 2 is an internal structural view of an EBSM printing apparatus according to an embodiment of the present application, which includes an electron gun 100 and a forming chamber 200. The electron gun includes a cathode 110 and an anode 120, and the EBSM printing apparatus emits an electron beam mainly through a high voltage or high Wen Jifa of the cathode 110 and deflects downward to a printing surface located in a forming chamber when processing, and makes an acceleration movement under the action of the anode 120. The powder metal on the printing surface is heated and melted under the action of the electron beam and solidifies rapidly as the electron beam is removed, thus being reciprocally processed to form the printing member.
Before predicting the lifetime of the cathode 110, the depth of poisoning of the cathode 110 needs to be modeled first by design experiments. An EBSM print test of different environmental variables was designed, in which a law was obtained that the poisoning depth of the cathode 110 varied with the passage of EBSM processing time under different air pressure conditions. After the poisoning depth model is established, the remaining life of the cathode 110 may be predicted according to the printing time of the EBSM printing apparatus in the actual use state, the air pressure value of the electron gun 100, the air pressure value of the forming cavity 200, and other data, in combination with the poisoning depth model.
When the EBSM printing device is actually used for EBSM printing, at least one acquisition point is respectively set in the electron gun 100 and the forming cavity 200, so as to acquire real-time online data acquisition of the cathode 110 in the printing process, and obtain the printing time of the EBSM printing process, the time air pressure value in the electron gun 100 and the actual air pressure value of the forming cavity 200. The number of the collection points may be one or more, and the collection points are respectively arranged at one or more positions in the electron gun 100 to obtain the air pressure value of the corresponding position; and acquiring the air pressure value at a corresponding position or positions in the forming cavity 200. The data collected by the online data collection is the real-time change value of the air pressure.
After the actual air pressure value of the electron gun 100 and the actual air pressure value of the forming cavity 200 are obtained, the air pressure value of the cathode 110 on the cathode emission surface in the EBSM printing process can be calculated and obtained by a finite element simulation mode. The real physical system such as geometry, load condition and the like can be simulated by using a mathematical approximation method through finite element simulation. Since the air pressure value on the emitting surface of the cathode 110 is inconvenient to directly measure and obtain, a mathematical model is used to perform analog calculation on the actual working condition. When the air pressure value of the emission surface of the cathode 110 in the actual EBSM printing process is obtained, the life value of the cathode 110 at this time can be calculated by combining the poisoning depth model of the cathode 110 obtained in the test, so as to predict the remaining life of the cathode 110.
The application provides a cathode life prediction method for the application of EBSM and other electron beam processing fields, which is based on a poisoning failure mechanism of a cathode to realize the prediction of the residual life of the cathode in the actual EBSM printing process, and has more accurate and reliable prediction effect. By predicting the remaining life of the cathode 110, the occurrence of defective workpieces can be avoided, and further, the direct or indirect economic loss caused by the failure of the workpieces in the application process is avoided, and the maintenance and repeated processing costs in the EBSM and other electron beam processing application processes are greatly reduced.
Fig. 3 is a flowchart of a method for establishing a poisoning depth model of a cathode according to an embodiment of the present application, wherein in one embodiment, the establishing the poisoning depth model of the cathode of the electron gun in the EBSM printing process includes the following steps S110 to S140.
S110: and fitting a life distribution model of the cathode according to the replacement time of the cathode of the electron gun in the historical statistical data.
S120: and selecting a plurality of preset observation points according to the life distribution model to respectively perform an EBSM printing test, and recording the test printing time, the test air pressure value of the electron gun and the test air pressure value of the forming cavity in real time in the test process.
S130: and stopping the printing test when reaching each preset observation point in the test process of each preset observation point, and acquiring the poisoning depth of the cathode at each preset observation point.
S140: for different preset air pressure values at each preset observation point, respectively constructing a change relation between the poisoning depth of the cathode emission surface and the printing time under different preset air pressure values in a curve fitting mode to be used as a poisoning depth model of the cathode; wherein the number of the poisoning depth models is not less than three.
Specifically, when a rule of variation of the poisoning depth of the cathode 110 with the passage of the EBSM processing time is obtained through a design test, a record of replacement of the cathode 110 in the electron gun 100 in the historical statistics data needs to be obtained first, and a life distribution model of the cathode 110 is fitted through a distribution function according to the replacement time of the cathode 110. Then, after the life distribution model of the cathode 110 is obtained, it is necessary to select a preset observation point required for the test by means of the life distribution model. By selecting a plurality of preset observation points to observe the EBSM printing test process, a more accurate poisoning depth model of the cathode 110 can be obtained.
After a plurality of preset observation points are selected, a poisoning depth test of the cathode 110 is performed, and a plurality of tests are performed for each preset observation point. To obtain multiple sets of test data, and prevent the accidental test from affecting the accuracy of the poisoning depth model. In this embodiment, the number of tests to be performed on the plurality of predicted observation points is not less than 3, so that not less than 3 sets of test data are obtained, and the reliability of the tests is improved. After the EBSM print test is started, the test processing time at the time of the print test, the test air pressure value inside the electron gun 100, and the test air pressure value inside the forming chamber 200 are recorded in real time, respectively. And stopping the printing test after the EBSM printing test is respectively carried out to the preset observation points. The cathode 110 in the electron gun 100 is taken out, and the poisoning depth of the emission surface of the cathode 110 at different times is measured by a test instrument. In this embodiment, an auger spectrometer is used to detect the depth of poisoning of the cathode 110. After each preset observation point is tested for 3 times, taking the average value of the 3 groups of poisoning depths as the poisoning depth value of the group of preset observation point tests. Cathode poisoning is generally a compound generated by reacting the material of the cathode 110 with a printing metal (e.g., ti, ni, al, fe, etc.) and a residual gas element (e.g., O, H, N, etc.), and thus, the above compound can be measured to determine the poisoning depth of the cathode 110.
The preset air pressure values at the preset observation points are different, that is, each preset air pressure value corresponds to a set of data of the printing time, the test air pressure value of the electron gun 100 and the test air pressure value of the forming cavity 200. Therefore, the relationship between the poisoning depth on the emission surface of the cathode 110 and the printing time is constructed by using curve fitting, and the obtained relationship model is used as the poisoning depth model of the cathode 110. Because the selected preset observation points are multiple, the test data obtained at the multiple preset observation points also have multiple groups, and multiple poisoning depth models can be built according to the multiple groups of data. In this embodiment, the number of poisoning depth models is not less than three. After the models of the poisoning depth are obtained, the poisoning depth model of the cathode 110 in the actual printing process can be obtained by interpolation according to the actual data and the poisoning depth models in the subsequent life prediction process.
Fig. 4 is a flowchart of a method for selecting a preset observation point according to an embodiment of the present application, wherein the selecting a plurality of preset observation points according to the lifetime distribution model includes the following steps S121 and S122.
S121: prolonging the life ofThe life estimation of the cathode at a preset confidence level in the life distribution model is used as a preset observation point x R 。
S122: at 0 to the preset observation point x R Selecting N preset observation points x 1 、x 2 ...x N And recording the preset observation point x 1 、x 2 ...x N 、x R The method comprises the steps of carrying out a first treatment on the surface of the Wherein N is greater than or equal to 4 and 0<x 1 <x 2 <x N <x R 。
When the preset observation point is selected, a preset lifetime estimated value at a higher confidence level in the lifetime distribution model can be used as the maximum value of observation. In this embodiment, the preset confidence level is 70%. That is, according to the life distribution model, a life estimate at 70% confidence is taken as a preset observation point x R Is the maximum point of (2). After the largest preset observation point is selected, the observation point x is from 0 to the preset observation point x R Selecting N preset observation points x 1 、x 2 ...x N . Wherein N is greater than or equal to 4 and 0<x 1 <x 2 <x N <x R . I.e. between 0 and x R Selecting at least 5 preset observation points (wherein the selected preset observation points do not contain 0 but must contain x) R ) For the preset observation point x 1 、x 2 ...x N 、x R Recording is carried out, and the distribution is used as a stopping point of a subsequent EBSM printing test.
In one embodiment, the lifetime distribution model is a lognormal distribution:
wherein x is the estimated lifetime of the cathode, f (x) is the distribution function of the estimated lifetime of the cathode, μ is the mean value of the estimated lifetime of the cathode, and σ is the standard deviation of the estimated lifetime of the cathode. In the present embodiment, a lognormal distribution formula is used to describe a life distribution model of the cathode 110. Where x is an estimate of the lifetime of the cathode 110, i.e., the effective use time of the cathode 110 in the EBSM printing device.
In one embodiment, the relationship between the poisoning depth of the cathode emission surface and the printing time at the preset air pressure value is:
d＝Aexp(-B/t 2 )；
wherein d is the poisoning depth of the cathode, t is the printing time, and A and B are constants related to the cathode material, the material processed in the EBSM printing process and the preset air pressure value. In this embodiment, a curve d=f (t) of the poisoning depth d of the cathode 110 in relation to the printing time t is constructed by a curve fitting method under the action of a preset air pressure p, and the general expression is d=axp (-B/t) 2 ). A and B are two different constants, and a and B are constants related to the material of the cathode 110, the processed material used in the printing process of the EBSM printing apparatus, the preset air pressure value, and the like.
Fig. 5 is a flowchart of a method for acquiring an emission surface air pressure value through finite element simulation according to an embodiment of the present application, in one embodiment, the electron gun includes a first vacuum pump, the forming cavity includes a second vacuum pump, and the acquiring the air pressure value of the emission surface of the cathode through finite element simulation includes the following steps S310 to S340.
S310: and taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure at the position of the first vacuum pump as an outlet, acquiring a first outlet pressure function or a first speed function of the electron gun, and applying the first outlet pressure function or the first speed function to the first vacuum pump.
S320: and taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure at the position of the second vacuum pump as an outlet, acquiring a second outlet pressure function or a second speed function of the forming cavity, and applying the second outlet pressure function or the second speed function to the second vacuum pump.
S330: and establishing a finite element model of a flow field in an actual printing process according to the first outlet pressure function and the second outlet pressure function or the first speed function and the second speed function.
S340: and extracting an air pressure average value in a preset area near the emitting surface of the cathode, and taking the air pressure average value as the air pressure value of the emitting surface of the cathode.
The EBSM printing apparatus further includes a first vacuum pump 130 and a second vacuum pump 210, where the first vacuum pump 130 is disposed inside the electron gun, and the second vacuum pump 210 is disposed inside the forming chamber, and is respectively used for providing vacuum environments required for electron beam propagation in the EBSM printing process. When the poisoning depth test is performed on different preset observation points, different preset air pressure values may be obtained by changing the working parameters of the first vacuum pump 130 and the second vacuum pump 210, so as to obtain at least 3 poisoning depth models under the action of the different preset air pressure values.
When the air pressure value on the emitting surface of the cathode 110 is obtained by a finite element simulation method, certain processing characteristics which do not affect the flow field need to be ignored first, and a finite element model of the flow field of the EBSM printing device in the printing process is established. When a flow field finite element model of the electron gun 100 in the EBSM printing process is built, the volatilization rate of the processed material needs to be taken as an inlet, the air pressure at the position of the first vacuum pump is taken as an outlet, and a first outlet pressure function or a first speed function of the electron gun 100 is obtained and applied to the first vacuum pump. Similarly, when establishing the flow field finite element model of the forming chamber 200 in the EBSM printing process, it is necessary to take the volatilization rate of the processed material as an inlet, and the air pressure at the location of the second vacuum pump as an outlet, to obtain a second outlet pressure function or a second velocity function of the forming chamber 200, and apply the second outlet pressure function or the second velocity function to the second vacuum pump.
And establishing a finite element model of the flow fields in the electron gun 100 and the forming cavity 200 during the actual printing process according to the obtained first outlet pressure function and the second outlet pressure function or the first speed function and the second speed function. According to the finite element model of the gas flow field in the electron gun 100 and the forming chamber 200 during processing, the gas pressure value in a certain area near the emission surface of the cathode 110 is extracted, and the average gas pressure in a certain area near the emission surface is calculated as the gas pressure value of the emission surface. Since the electron beam needs to be emitted from the emitting surface of the cathode 110, the air pressure value on the emitting surface is inconvenient to directly measure and obtain, and therefore, the air pressure value on the emitting surface of the cathode 110 needs to be obtained by performing simulation calculation on the actual working condition through a finite element model. When the air pressure value of the emission surface of the cathode 110 in the actual EBSM printing process is obtained, the life value of the cathode 110 at this time can be calculated by combining the poisoning depth model of the cathode 110 obtained in the test, so as to predict the remaining life of the cathode 110.
In one embodiment, when establishing a finite element model of the flow field during actual printing, the model may also be modified using actual air pressure values acquired by the acquisition points in the electron gun and in the forming chamber. And correcting the finite element model obtained in the step by taking the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity which are collected at one or more collecting points in the electron gun and the forming cavity as correcting points so as to obtain an accurate finite element model of the flow field, thereby improving the prediction accuracy.
Fig. 6 is a flowchart of a method for creating a finite element model of a flow field according to one embodiment of the present application, wherein predicting the residual life of the cathode according to the barometric pressure value of the emission surface and the poisoning depth model includes the following steps S410 to S430.
S410: and interpolating an actual poisoning depth model of the cathode under the air pressure value of the emission surface by using the air pressure value of the emission surface as a reference through at least three poisoning depth models.
S420: and acquiring a service life value of the cathode under a preset confidence coefficient according to the actual poisoning depth model and the actual printing time.
S430: the remaining lifetime of the cathode is the difference between the lifetime value and the actual printing time.
After the air pressure value of the surface of the emission surface of the cathode 110 is obtained, the air pressure value of the emission surface is used as a reference, and the actual poisoning depth model of the cathode under the air pressure value of the emission surface is obtained by interpolation by using at least three poisoning depth models under different preset air pressure values obtained in the poisoning depth modeling process. Since the actual poisoning depth model is a variation relationship between the poisoning depth d of the emission surface of the cathode 110 and the printing time t under a certain air pressure value, after the printing time in the actual printing process is obtained, the life value of the cathode 110 under the preset confidence coefficient, that is, the life value under the 70% confidence coefficient, can be obtained according to the actual poisoning depth model. After obtaining the lifetime value of the cathode 110 under the preset confidence, the remaining lifetime of the cathode 110 is obtained, where the remaining lifetime of the cathode 110 is the difference between the lifetime value and the actual printing time. The service life of the cathode can be accurately predicted by the cathode service life prediction method provided by the application.
Fig. 7 is a flowchart of a method for predicting the residual life of a cathode according to one embodiment of the present application, in which the interpolating the actual poisoning depth model of the cathode at the air pressure value of the emission surface by not less than three poisoning depth models includes the following steps S411 to S412.
S411: fitting relation between the parameter A and the parameter B and the air pressure value through the poisoning depth models which are not less than three.
S412: and acquiring the values of the parameter A and the parameter B under the air pressure value of the emission surface according to the relation between the parameter A and the parameter B and the air pressure value respectively so as to establish an actual poisoning depth model of the cathode under the air pressure value of the emission surface.
Fitting the relation between the parameters A and B and the air pressure value p and the printing time t according to the poisoning depth model, and calculating the air pressure value p on the actual emitting surface according to the printing time 0 Lower B 0 And A 0 Values. According to the calculated A 0 、B 0 Constructing an air pressure value p at the actual emitting surface 0 The poisoning depth model of the cathode 110 is described below. And calculating the poisoning depth of the cathode 110 by the processed time, so that the service life of the cathode 110 under the 70% confidence coefficient is calculated by using the poisoning depth, and the difference between the service life value and the processed time is the residual service life of the cathode 110.
In one embodiment, the relationship between the parameter a and the air pressure value is:
A＝C*t 2 *p*exp(-1/p)；
the relation between the parameter B and the air pressure value is as follows:
B＝-t 2 /p；
wherein t is printing time, p is an air pressure value, and C is a constant related to the air pressure value p.
In the above process, the relation between the parameter a and the parameter B, the air pressure value p and the printing time t is fitted according to the above poisoning depth models, and the relation between the parameter a and the air pressure value p obtained by fitting is a=c×t 2 * p is exp (-1/p), and the relation between the parameter B and the air pressure value p is B= -t 2 And/p. Wherein C is a constant, the value of which is related to the value of the air pressure value p. The relation between the parameters A and B and the air pressure value p can be used to calculate the air pressure value p of the actual emitting surface 0 Lower B 0 And A 0 Values to construct the actual air pressure value p at the emitting surface 0 The poisoning depth model of the cathode 110 is described below. Because the service life of the cathode 110 depends on the poisoning depth of the cathode 110, the cathode life prediction method provided by the application is based on the poisoning failure mechanism of the cathode to realize the prediction of the residual life of the cathode in the actual EBSM printing process, and the prediction effect is more accurate and reliable.
It should be understood that, although the steps in the flowcharts of fig. 1 and 3-7 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps of FIGS. 1, 3-7 may include steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages in other steps.
In the description of the present specification, reference to the terms "some embodiments," "other embodiments," "desired embodiments," and the like, means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic descriptions of the above terms do not necessarily refer to the same embodiment or example.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (5)
1. A cathode life prediction method, characterized by being applied to an EBSM printing apparatus, the EBSM printing apparatus including an electron gun including a cathode therein and a forming chamber, the cathode life prediction method comprising:
performing an EBSM printing test on the EBSM printing device, and establishing a poisoning depth model of a cathode of the electron gun in an EBSM printing process;
at least one acquisition point is respectively arranged in the electron gun and the forming cavity, and when the EBSM printing operation is actually performed, the actual printing time, the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity are acquired and recorded in real time;
the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity are combined, and the air pressure value of the emitting surface of the cathode is obtained in a finite element simulation mode;
predicting the residual life of the cathode according to the air pressure value of the emission surface and the poisoning depth model;
the establishing the poisoning depth model of the cathode of the electron gun in the EBSM printing process comprises the following steps:
fitting a life distribution model of the cathode according to the replacement time of the cathode of the electron gun in the historical statistical data;
selecting a plurality of preset observation points according to the life distribution model to respectively perform an EBSM printing test, and recording the test printing time, the test air pressure value of the electron gun and the test air pressure value of the forming cavity in real time in the test process;
stopping printing test when reaching each preset observation point in the test process of each preset observation point, and obtaining the poisoning depth of the cathode at each preset observation point;
for different preset emission surface air pressure values at each preset observation point, respectively constructing a change relation between the poisoning depth of the cathode emission surface and the printing time under the different preset emission surface air pressure values in a curve fitting mode to be used as a poisoning depth model of the cathode; wherein the number of the poisoning depth models is not less than three;
the relation between the poisoning depth of the cathode emission surface and the printing time under the preset emission surface air pressure value is as follows:
d＝Aexp(-B/t 2 )；
wherein d is the poisoning depth of the cathode, t is the printing time, and A and B are constants related to the cathode material, the material processed in the EBSM printing process and the preset emission surface air pressure value;
the predicting the residual life of the cathode according to the air pressure value of the emission surface and the poisoning depth model comprises:
taking the air pressure value of the emission surface as a reference, and interpolating an actual poisoning depth model of the cathode under the air pressure value of the emission surface through at least three poisoning depth models;
acquiring a service life value of the cathode under a preset confidence coefficient according to the actual poisoning depth model and the actual printing time;
the residual life of the cathode is the difference between the life value and the actual printing time;
the interpolating the actual poisoning depth model of the cathode at the air pressure value of the emission surface by not less than three poisoning depth models includes:
fitting a relation between the parameter A and the parameter B and the emission surface air pressure value through the poisoning depth models with at least three values;
according to the relation between the parameter A and the parameter B and the emission surface air pressure value, acquiring the values of the parameter A and the parameter B under the emission surface air pressure value to establish an actual poisoning depth model of the cathode under the emission surface air pressure value;
the relation between the parameter A and the emission surface air pressure value is as follows:
A＝C*t 2 *p*exp(-1/p)；
the relation between the parameter B and the emission surface air pressure value is as follows:
B＝-t 2 /p；
wherein t is printing time, p is emission surface air pressure value, and C is a constant related to the emission surface air pressure value p.
2. The method according to claim 1, wherein selecting a plurality of preset observation points according to the lifetime distribution model comprises:
taking the estimated life of the cathode at a preset confidence level in the life distribution model as a preset observation pointx R ；
At 0 to the preset observation point x R Selecting N preset observation points x 1 、x 2 ...x N And recording the preset observation point x 1 、x 2 ...x N 、x R The method comprises the steps of carrying out a first treatment on the surface of the Wherein N is greater than or equal to 4 and 0<x 1 <x 2 <x N <x R 。
3. The cathode life prediction method according to claim 2, wherein the life distribution model is a lognormal distribution:
wherein x is the estimated lifetime of the cathode, f (x) is the distribution function of the estimated lifetime of the cathode, μ is the mean value of the estimated lifetime of the cathode, and σ is the standard deviation of the estimated lifetime of the cathode.
4. The method of claim 1, wherein the electron gun comprises a first vacuum pump, the forming chamber comprises a second vacuum pump, and the obtaining the air pressure value of the emission surface of the cathode by means of finite element simulation comprises:
taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure at the position of the first vacuum pump as an outlet, acquiring a first outlet pressure function or a first speed function of the electron gun, and applying the first outlet pressure function or the first speed function to the first vacuum pump;
taking the volatilization rate of the processed material in the EBSM printing process as an inlet, taking the air pressure at the position of the second vacuum pump as an outlet, acquiring a second outlet pressure function or a second speed function of the forming cavity, and applying the second outlet pressure function or the second speed function to the second vacuum pump;
establishing a finite element model of a flow field in an actual printing process according to the first outlet pressure function and the second outlet pressure function or the first speed function and the second speed function;
and extracting an air pressure average value in a preset area near the emitting surface of the cathode, and taking the air pressure average value as the air pressure value of the emitting surface of the cathode.
5. The method for predicting the lifetime of a cathode in accordance with claim 4, wherein said modeling the finite element model of the flow field during actual printing further comprises:
and correcting the finite element model by taking the actual air pressure value of the electron gun and the actual air pressure value of the forming cavity as correction points so as to obtain an accurate finite element model of the flow field.
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