CN116913434A - Method and device for improving mechanical properties of titanium alloy based on laser shock peening - Google Patents
Method and device for improving mechanical properties of titanium alloy based on laser shock peening Download PDFInfo
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- 229910001069 Ti alloy Inorganic materials 0.000 title claims abstract description 166
- 230000035939 shock Effects 0.000 title claims abstract description 141
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 37
- 230000006872 improvement Effects 0.000 claims abstract description 10
- 238000012549 training Methods 0.000 claims description 34
- 238000005457 optimization Methods 0.000 claims description 20
- 230000003746 surface roughness Effects 0.000 claims description 17
- 238000011156 evaluation Methods 0.000 claims description 13
- 238000007670 refining Methods 0.000 claims description 4
- 229910003460 diamond Inorganic materials 0.000 claims description 3
- 239000010432 diamond Substances 0.000 claims description 3
- 238000003825 pressing Methods 0.000 claims description 3
- 238000013473 artificial intelligence Methods 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 29
- 239000000463 material Substances 0.000 description 17
- 238000011160 research Methods 0.000 description 8
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- 230000008859 change Effects 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
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- 238000005299 abrasion Methods 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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- 230000001419 dependent effect Effects 0.000 description 1
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- 238000003860 storage Methods 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C60/00—Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The application relates to an artificial intelligence technology, and discloses a method for improving mechanical properties of a titanium alloy based on laser shock peening, which comprises the following steps: generating subject data of the titanium alloy; generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data, generating mechanical parameters and a standard curve of the laser shock reinforced titanium alloy according to the experimental data, and performing region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve; carrying out sample refinement on the regional curve by using a preset interpolation algorithm to obtain a refinement variable of the regional curve; and generating the optimal performance improvement parameters of the laser shock reinforced titanium alloy by using the refinement variables. The application further provides a device for improving the mechanical properties of the titanium alloy based on laser shock peening. The application can improve the mechanical property of the titanium alloy based on laser shock peening.
Description
Technical Field
The application relates to the technical field of artificial intelligence, in particular to a method and a device for improving mechanical properties of titanium alloy based on laser shock peening.
Background
Titanium alloy is a structural material with wider application due to a series of advantages of higher specific strength, lower density, stronger corrosion resistance and fatigue resistance. In the service environment with the service temperature lower than 800 ℃, the titanium alloy has very remarkable advantages and is widely applied to the fields of aviation, automobiles, energy sources and the like. Under the action of long-time high temperature and impact load, the titanium alloy part has potential safety hazards of losing bearing capacity, and the improvement of the fatigue resistance of the titanium alloy has important significance for the safety of an aeroengine and the development of aerospace industry, so how to improve the mechanical properties of the titanium alloy is a problem to be solved urgently.
Disclosure of Invention
The application provides a method and a device for improving mechanical properties of a titanium alloy based on laser shock reinforcement, and mainly aims to solve the problem of improving the mechanical properties of the titanium alloy.
In order to achieve the above purpose, the application provides a method for improving mechanical properties of titanium alloy based on laser shock peening, comprising the following steps:
acquiring historical data of titanium alloy, and performing topic classification on the historical data to obtain topic data of the historical data;
generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data, and generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data;
generating a standard curve of the experimental data according to the subject and the mechanical parameter, and carrying out region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve;
carrying out sample refinement on the regional curve by using a preset interpolation algorithm to obtain a refinement variable of the regional curve;
generating optimization parameters of the laser shock reinforced titanium alloy by using the refinement variables, and determining the optimization parameters as optimal performance improvement parameters of the laser shock reinforced titanium alloy.
Optionally, the performing topic classification on the historical data to obtain topic data of the historical data includes:
acquiring a training set, and calculating Euclidean distance between the historical data and each training data in the training set by using an Euclidean distance algorithm;
selecting a preset number of Euclidean distances as target distances from small to large according to the distance values, and generating the maximum topic probability of the training data according to the target distances;
and determining the theme of the historical data according to the maximum theme probability, and collecting the historical data and the theme corresponding to the historical data as theme data.
Optionally, the calculating the euclidean distance between the historical data and each training data in the training set by using the euclidean distance algorithm includes:
and calculating the Euclidean distance between the historical data and each training data in the training set by using the following Euclidean distance algorithm:
wherein d represents the distance, w, between the history data and the training data 1j Representing the history data, w 2j And representing the training data, j represents the j-th data in the historical data, and n represents the total data number of the historical data.
Optionally, the generating experimental data of the laser shock peening titanium alloy according to the subject of the subject data includes:
determining experimental factors of the laser shock reinforced titanium alloy according to the subject, and generating experimental conditions of the laser shock reinforced titanium alloy according to the experimental factors;
and generating experimental data of the laser shock reinforced titanium alloy by using the experimental conditions.
Optionally, the generating the mechanical parameters of the laser shock peening titanium alloy according to the experimental data includes:
generating the surface roughness of the laser shock reinforced titanium alloy according to the experimental data;
generating a microhardness value of the laser shock reinforced titanium alloy according to the experimental data and a preset microhardness algorithm;
generating residual stress of the laser shock reinforced titanium alloy according to the experimental data, and determining mechanical parameters of the laser shock reinforced titanium alloy according to the surface roughness, the microhardness value and the residual stress.
Optionally, the generating the surface roughness of the laser shock peening titanium alloy according to the experimental data includes:
generating a three-dimensional surface profile function of the laser shock reinforced titanium alloy according to the experimental data, and generating an evaluation reference plane of the laser shock reinforced titanium alloy according to the three-dimensional surface profile function and a preset Gaussian low-pass filter;
and generating the surface roughness of the laser shock reinforced titanium alloy according to the evaluation reference plane and the three-dimensional surface profile function.
Optionally, the generating the microhardness value of the laser shock reinforced titanium alloy according to the experimental data and a preset microhardness algorithm includes:
acquiring hardness data of a microhardness meter in the experimental data;
generating microhardness values of the laser shock peening titanium alloy using the hardness data and a microhardness algorithm:
wherein H is v Is the microhardness value of the laser shock reinforced titanium alloy, P is the loading load in the hardness data, d is the diagonal length of the impression of the laser shock reinforced titanium alloy surface, and alpha is the included angle of two opposite sides of the diamond pressing head in the hardness data.
Optionally, the generating the standard curve of the experimental data according to the subject and the mechanical parameter includes:
establishing a blank coordinate system, and determining coordinate elements of the blank coordinate system according to the theme and the mechanical parameters;
generating discrete points of the blank coordinate system according to the coordinate elements and the experimental data, and determining a theoretical function of a standard curve to be fitted by using the discrete points;
calculating a fitting error value of the experimental data according to the theoretical function and a preset fitting algorithm, and generating a standard curve of the experimental data according to the fitting error value, wherein the preset fitting algorithm is as follows:
wherein L is the fitting error value of the experimental data, y i Is the experimental data, f (x) is the theoretical function, i is the ith data in the experimental data, and m is the total number of data in the experimental data.
Optionally, the area selection is performed on the standard curve according to a preset interval threshold to obtain an area curve of the standard curve, which includes:
determining a target endpoint of the standard curve according to a preset interval threshold value, and determining a target area of the standard curve according to the target endpoint;
and generating a region curve of the standard curve by using the target region and the standard curve.
In order to solve the above problems, the present application further provides a device for improving mechanical properties of titanium alloy based on laser shock peening, the device comprising:
the topic classification module is used for acquiring historical data of the titanium alloy, and performing topic classification on the historical data to obtain topic data of the historical data;
the mechanical parameter module is used for generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data and generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data;
the region selection module is used for generating a standard curve of the experimental data according to the subject and the mechanical parameter, and performing region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve;
the sample refining module is used for refining the samples of the regional curve by using a preset interpolation algorithm to obtain refined variables of the regional curve;
and the optimization parameter module is used for generating the optimization parameters of the laser shock reinforced titanium alloy by using the refinement variables, and determining the optimization parameters as the optimal performance improvement parameters of the laser shock reinforced titanium alloy.
According to the embodiment of the application, the historical data of the titanium alloy is subject classified, so as to determine experimental influence factors of the titanium alloy, lay a foundation for the research of the laser shock reinforced titanium alloy, and provide a definite research path for the laser shock reinforced titanium alloy, experimental data of the laser shock reinforced titanium alloy is generated according to the subject of the subject data, mechanical parameters of the laser shock reinforced titanium alloy are generated according to the experimental data, the mechanical parameters are necessary for the research of the performance of the laser shock reinforced titanium alloy, are key parameters for measuring the mechanical performance of the laser shock reinforced titanium alloy, a standard curve of the experimental data is generated, region selection is performed on the standard curve according to a preset interval threshold, and the initial optimization of experimental conditions of the laser shock reinforced titanium alloy is performed.
Drawings
FIG. 1 is a schematic flow chart of a method for improving mechanical properties of a titanium alloy based on laser shock peening according to an embodiment of the present application;
FIG. 2 is a flow chart of the subject classification of historical data according to an embodiment of the application;
FIG. 3 is a flow chart illustrating the generation of mechanical parameters according to an embodiment of the present application;
FIG. 4 is a functional block diagram of a device for improving mechanical properties of a titanium alloy based on laser shock peening according to an embodiment of the present application;
the achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides a method for improving mechanical properties of a titanium alloy based on laser shock peening. The execution main body of the method for improving the mechanical properties of the titanium alloy based on laser shock peening comprises at least one of electronic equipment, such as a service end and a terminal, which can be configured to execute the method provided by the embodiment of the application. In other words, the method for improving the mechanical properties of the titanium alloy based on laser shock peening can be performed by software or hardware installed in terminal equipment or service equipment. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a schematic flow chart of a method for improving mechanical properties of a titanium alloy based on laser shock peening according to an embodiment of the present application is shown. In this embodiment, the method for improving mechanical properties of a titanium alloy based on laser shock peening includes:
s1, acquiring historical data of titanium alloy, and performing topic classification on the historical data to obtain topic data of the historical data.
In the embodiment of the application, the historical data of the titanium alloy refers to experimental data when mechanical properties of the titanium alloy are detected, and the experimental data include but are not limited to: the method comprises the steps of selecting a chemical component of a titanium alloy, a size of the titanium alloy, a quality of the titanium alloy, a constraint layer, an absorption layer, an instrument used in an experiment and instrument parameters of the instrument.
Further, historical data of the titanium alloy was obtained in order to form a control group with the laser shock reinforced titanium alloy, which was studied using some characteristics of the historical data of the titanium alloy.
In an embodiment of the present application, referring to fig. 2, the classifying the subject of the history data to obtain subject data of the history data includes:
s21, acquiring a training set, and calculating Euclidean distances between the historical data and each training data in the training set by using an Euclidean distance algorithm;
s22, selecting a preset number of Euclidean distances as target distances from small to large according to distance values, and generating the maximum topic probability of the training data according to the target distances;
s23, determining the theme of the historical data according to the maximum theme probability, and collecting the historical data and the theme corresponding to the historical data as theme data.
In detail, the subject classification of the historical data is to determine experimental influence factors of the titanium alloy, lay a foundation for the laser shock reinforced titanium alloy research, and provide a clear research path for the laser shock reinforced titanium alloy.
In detail, the generating the maximum topic probability of the training data according to the target distance refers to selecting one topic with the largest occurrence frequency of the training data from all target distances, wherein the maximum topic probability can be determined from the topics, and because the selected target distance is the minimum distance value, the topic to which the training data corresponding to the target distance belongs is most likely to be the topic to which the historical data belongs.
In detail, the calculating the euclidean distance between the historical data and each training data in the training set by using the euclidean distance algorithm includes:
and calculating the Euclidean distance between the historical data and each training data in the training set by using the following Euclidean distance algorithm:
wherein d represents the distance, w, between the history data and the training data 1j Representing the history data, w 2j And representing the training data, j represents the j-th data in the historical data, and n represents the total data number of the historical data.
In detail, the Euclidean distance algorithm is simple and small in calculation amount, and the similarity of the historical data and the training data can be displayed quickly and conveniently.
S2, generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data, and generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data.
In the embodiment of the application, the experimental data of the laser shock reinforced titanium alloy is generated according to the subject of the subject data, and the experimental data of the laser shock reinforced titanium alloy is performed according to the subject because the historical data of the titanium alloy provides a theoretical basis and an experimental direction for the experiment of the laser shock reinforced titanium alloy.
In detail, the experimental data includes, but is not limited to: the experimental environment of the laser shock reinforced titanium alloy, the quality of the laser shock reinforced titanium alloy, the size of the laser shock reinforced titanium alloy, the experimental parameters of laser strengthening, the use instrument, the laser energy and the power density, and the like, wherein the use instrument comprises but is not limited to: the device comprises a laser generator, a laser control unit, a five-axis linkage numerical control workbench, a program control box-type resistance furnace and the like.
In an embodiment of the present application, the generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data includes:
determining experimental factors of the laser shock reinforced titanium alloy according to the subject, and generating experimental conditions of the laser shock reinforced titanium alloy according to the experimental factors;
and generating experimental data of the laser shock reinforced titanium alloy by using the experimental conditions.
In detail, experimental factors of the laser shock peening titanium alloy include, but are not limited to: the laser comprises a constraint layer, an absorption layer, a laser wavelength, a pulse width, a pulse frequency, laser energy and a light spot diameter; the experimental conditions of the laser shock peening titanium alloy can be as follows: the restriction layer is made of K9 optical glass, the absorption layer is made of aluminum foil, the laser wavelength is 1064nm, the pulse width is 10ns, the pulse frequency is 1HZ, the laser energy is 8J, and the spot diameter is 3mm.
Further, the mechanical parameters may be: surface roughness, microhardness value, residual stress and other mechanical performance parameters.
In an embodiment of the present application, referring to fig. 3, the generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data includes:
s31, generating the surface roughness of the laser shock reinforced titanium alloy according to the experimental data;
s32, generating a microhardness value of the laser shock reinforced titanium alloy according to the experimental data and a preset microhardness algorithm;
s33, generating residual stress of the laser shock reinforced titanium alloy according to the experimental data, and determining mechanical parameters of the laser shock reinforced titanium alloy according to the surface roughness, the microhardness value and the residual stress.
In detail, the surface morphology of a metal material is formed on the processing surface of the material by the roughness and waviness thereof, and the microscopic aggregate morphology formed by fine gaps and concave-convex with small fluctuation is the surface roughness, which is a parameter capable of reflecting the geometric characteristics of the surface of the material. Roughness is an important performance index of a material, because it directly represents various characteristics of the material such as abrasion resistance, contact stiffness, fatigue limit and the like. The conventional roughness measuring instrument can only obtain a two-dimensional profile, is insufficient for describing the grain characteristics of the surface of the material, and cannot comprehensively and reliably reflect the microscopic morphology of the surface of the material. However, the three-dimensional roughness test and evaluation can well express the microstructure and morphology of the material surface, so that the three-dimensional measurement and evaluation of the morphology and roughness of the material surface are necessary.
In detail, when the material is subjected to concentrated loads, non-uniform plastic deformation occurs, which in turn leads to the formation of residual stresses. The residual stress has a great adverse effect on the mechanical properties of the material.
In detail, the generating the surface roughness of the laser shock peening titanium alloy according to the experimental data includes:
generating a three-dimensional surface profile function of the laser shock reinforced titanium alloy according to the experimental data, and generating an evaluation reference plane of the laser shock reinforced titanium alloy according to the three-dimensional surface profile function and a preset Gaussian low-pass filter;
and generating the surface roughness of the laser shock reinforced titanium alloy according to the evaluation reference plane and the three-dimensional surface profile function.
In detail, the generating the evaluation reference plane of the laser shock reinforced titanium alloy according to the three-dimensional surface profile function and a preset gaussian low pass filter may generate the evaluation reference plane by using the following reference algorithm:
Z 2 (x,y)＝Z 1 (x,y)*h(x,y)
wherein Z is 2 (x, y) is the evaluation reference plane, Z 1 (x, y) is the three-dimensional surface profile function and h (x, y) is the filter function of the Gao Sidi pass filter.
In detail, the roughness relationship of the surface roughness of the laser shock peening titanium alloy, the evaluation reference surface, and the three-dimensional surface profile function may be established using the following roughness algorithm:
Z 1 (x,y)＝Z 2 (x,y)+Z(x,y)
wherein Z is 1 (x, y) is the three-dimensional surface profile function, Z 2 (x, y) is the evaluation reference plane, and Z (x, y) is the surface roughness of the laser shock peening titanium alloy.
Further, the roughness relation and the reference surface algorithm are utilized to generate the surface roughness of the laser shock reinforced titanium alloy.
In detail, the generating the microhardness value of the laser shock reinforced titanium alloy according to the experimental data and a preset microhardness algorithm includes:
acquiring hardness data of a microhardness meter in the experimental data;
generating microhardness values of the laser shock peening titanium alloy using the hardness data and a microhardness algorithm:
wherein H is v Is the microhardness value of the laser shock reinforced titanium alloy, P is the loading load in the hardness data, d is the diagonal length of the impression of the laser shock reinforced titanium alloy surface, and alpha is the included angle of two opposite sides of the diamond pressing head in the hardness data.
In detail, hardness means a characteristic of a material that locally resists penetration of hard objects into its surface, and can be used to reflect the degree of hardness of a metal. Hardness can be interpreted as the level of resistance of a material to elastic, plastic deformation, or failure, as well as the level of resistance of a material to residual deformation and reverse failure. The hardness characterizes various properties of the material such as elasticity, plasticity, strength, wear resistance and the like. In general, the higher the hardness of a material, the higher the strength of the material, and the change of the hardness can reflect the strength.
S3, generating a standard curve of the experimental data according to the subject and the mechanical parameter, and carrying out region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve.
In the embodiment of the application, the standard curve shows the relevance, the change trend and the optimal interval among the experimental data, and the optimal parameter for improving the mechanical property of the laser shock reinforced titanium alloy can be judged according to the change trend and the optimal interval.
In detail, the region selection of the standard curve according to the preset interval threshold is to initially obtain the optimization parameters of the laser shock reinforced titanium alloy, and an optimization direction is provided for experiments.
In an embodiment of the present application, the generating the standard curve of the experimental data according to the subject and the mechanical parameter includes:
establishing a blank coordinate system, and determining coordinate elements of the blank coordinate system according to the theme and the mechanical parameters;
generating discrete points of the blank coordinate system according to the coordinate elements and the experimental data, and determining a theoretical function of a standard curve to be fitted by using the discrete points;
calculating a fitting error value of the experimental data according to the theoretical function and a preset fitting algorithm, and generating a standard curve of the experimental data according to the fitting error value, wherein the preset fitting algorithm is as follows:
wherein L is the fitting error value of the experimental data, y i Is the experimental data, f (x) is the theoretical function, i is the ith data in the experimental data, and m is the total number of data in the experimental data.
In detail, the coordinate elements refer to meanings and units represented by an abscissa and an ordinate of the blank coordinate system; and taking the theme as the abscissa of the blank coordinate system, and taking the mechanical parameter as the ordinate of the blank coordinate system.
In detail, the theoretical function is determined according to the distribution of the discrete points, and the theoretical function polynomial function can be embodied in linear, parabolic, waveform and the like; the fitting error value reflects the deviation of the experimental data and the theoretical function, and the fitting error value can be optimized by adjusting polynomial coefficients of the theoretical function and combining a loss function.
In the embodiment of the present application, the area selection is performed on the standard curve according to a preset interval threshold to obtain an area curve of the standard curve, including:
determining a target endpoint of the standard curve according to a preset interval threshold value, and determining a target area of the standard curve according to the target endpoint;
and generating a region curve of the standard curve by using the target region and the standard curve.
In detail, the target endpoint may be represented by an abscissa of the endpoint; the area curve of the standard curve is generated in order to select the appropriate experimental conditions that can reach the experimental expectations.
S4, carrying out sample refinement on the regional curve by using a preset interpolation algorithm to obtain a refinement variable of the regional curve.
In the embodiment of the application, the interpolation method is a method of inserting required intermediate values which are not listed in some tables into known function tables, so that more experimental data can be obtained, and the performance improvement parameters of the laser shock reinforced titanium alloy can be more accurately determined.
In the embodiment of the present application, the preset interpolation algorithm is:
wherein y (x) is an interpolation polynomial of the region curve, x is an argument of the interpolation polynomial, x is a curve abscissa in a curve section of the region curve, x j Is the abscissa, x, of the jth interpolation point of the region curve k Is the abscissa, y, of the kth interpolation point of the region curve k And k is the identification of the interpolation points, j is the identification of the interpolation points, and n is the total number of the interpolation points.
Further, assuming that the definition field of the original area curve is (2, 10), points in the definition field are defined by 3 explicit coordinates, but coordinate points are defined at the optimal experimental condition, the points in the definition field need to be refined to determine the coordinate points therein when the optimal experimental condition is present.
In detail, the refinement variables may be one or more, for example: at independent variables 10, 50 and 100, the dependent variable values are all 1;
s5, generating optimization parameters of the laser shock reinforced titanium alloy by using the refinement variables, and determining the optimization parameters as optimal performance improvement parameters of the laser shock reinforced titanium alloy.
In the embodiment of the application, the optimized parameters refer to specific experimental conditions of the laser shock reinforced titanium alloy, for example: the power density is 1, the pulse width is 17, the light spot size is 2, the beam energy is 90, the impact times are 100, and the like; and determining the optimized parameters as optimal performance improvement parameters, namely performing laser shock peening on the titanium alloy by taking the optimized parameters as experimental conditions.
According to the embodiment of the application, the historical data of the titanium alloy is subject classified, so as to determine experimental influence factors of the titanium alloy, lay a foundation for the research of the laser shock reinforced titanium alloy, and provide a definite research path for the laser shock reinforced titanium alloy, experimental data of the laser shock reinforced titanium alloy is generated according to the subject of the subject data, mechanical parameters of the laser shock reinforced titanium alloy are generated according to the experimental data, the mechanical parameters are necessary for the research of the performance of the laser shock reinforced titanium alloy, are key parameters for measuring the mechanical performance of the laser shock reinforced titanium alloy, a standard curve of the experimental data is generated, region selection is performed on the standard curve according to a preset interval threshold, and the initial optimization of experimental conditions of the laser shock reinforced titanium alloy is performed.
Fig. 4 is a functional block diagram of a device for improving mechanical properties of a titanium alloy based on laser shock peening according to an embodiment of the present application.
The titanium alloy mechanical property improving device 100 based on laser shock peening can be installed in electronic equipment. According to the functions implemented, the laser shock peening-based mechanical property improving device 100 may include a topic classification module 101, a mechanical parameter module 102, a region selection module 103, a sample refinement module 104, and an optimization parameter module 105. The module of the application, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the topic classification module 101 is configured to obtain historical data of a titanium alloy, and perform topic classification on the historical data to obtain topic data of the historical data;
the mechanical parameter module 102 is configured to generate experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data, and generate mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data;
the region selection module 103 is configured to generate a standard curve of the experimental data according to the subject and the mechanical parameter, and perform region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve;
the sample refinement module 104 is configured to refine samples of the area curve by using a preset interpolation algorithm, so as to obtain a refinement variable of the area curve;
the optimization parameter module 105 is configured to generate an optimization parameter of the laser shock reinforced titanium alloy by using the refinement variable, and determine the optimization parameter as an optimal performance improvement parameter of the laser shock reinforced titanium alloy.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application that uses a digital computer or a digital computer-controlled machine to simulate, extend and expand human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the apparatus claims can also be implemented by means of one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present application without departing from the spirit and scope of the technical solution of the present application.
Claims (10)
1. The method for improving the mechanical properties of the titanium alloy based on laser shock peening is characterized by comprising the following steps of:
acquiring historical data of titanium alloy, and performing topic classification on the historical data to obtain topic data of the historical data;
generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data, and generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data;
generating a standard curve of the experimental data according to the subject and the mechanical parameter, and carrying out region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve;
sample refinement is carried out on the region curve by using a preset interpolation algorithm to obtain a refinement variable of the region curve, wherein the preset interpolation algorithm is as follows:
wherein y (x) is an interpolation polynomial of the region curve, x is an argument of the interpolation polynomial, x is a curve abscissa in a curve section of the region curve, x j Is the abscissa, x, of the jth interpolation point of the region curve k Is the abscissa, y, of the kth interpolation point of the region curve k The interpolation ordinate is corresponding to the kth interpolation point abscissa, k is the identification of the interpolation point, j is the identification of the interpolation point, and n is the total number of the interpolation points;
generating optimization parameters of the laser shock reinforced titanium alloy by using the refinement variables, and determining the optimization parameters as optimal performance improvement parameters of the laser shock reinforced titanium alloy.
2. The method for improving mechanical properties of a titanium alloy based on laser shock peening of claim 1, wherein said performing a topic classification on said historical data to obtain topic data of said historical data comprises:
acquiring a training set, and calculating Euclidean distance between the historical data and each training data in the training set by using an Euclidean distance algorithm;
selecting a preset number of Euclidean distances as target distances from small to large according to the distance values, and generating the maximum topic probability of the training data according to the target distances;
and determining the theme of the historical data according to the maximum theme probability, and collecting the historical data and the theme corresponding to the historical data as theme data.
3. The method for improving mechanical properties of titanium alloy based on laser shock peening according to claim 2, wherein said calculating euclidean distance between said history data and each training data in said training set using euclidean distance algorithm comprises:
and calculating the Euclidean distance between the historical data and each training data in the training set by using the following Euclidean distance algorithm:
wherein d represents the distance, w, between the history data and the training data 1j Representing the history data, w 2j And representing the training data, j represents the j-th data in the historical data, and n represents the total data number of the historical data.
4. The method for improving mechanical properties of a titanium alloy based on laser shock peening as defined in claim 1, wherein said generating experimental data of the laser shock peening titanium alloy according to the subject of the subject data comprises:
determining experimental factors of the laser shock reinforced titanium alloy according to the subject, and generating experimental conditions of the laser shock reinforced titanium alloy according to the experimental factors;
and generating experimental data of the laser shock reinforced titanium alloy by using the experimental conditions.
5. The method for improving mechanical properties of a titanium alloy based on laser shock peening as defined in claim 1, wherein said generating mechanical parameters of the laser shock peening titanium alloy from the experimental data comprises:
generating the surface roughness of the laser shock reinforced titanium alloy according to the experimental data;
generating a microhardness value of the laser shock reinforced titanium alloy according to the experimental data and a preset microhardness algorithm;
generating residual stress of the laser shock reinforced titanium alloy according to the experimental data, and determining mechanical parameters of the laser shock reinforced titanium alloy according to the surface roughness, the microhardness value and the residual stress.
6. The method for improving mechanical properties of a titanium alloy based on laser shock peening as defined in claim 5, wherein said generating the surface roughness of the laser shock peening titanium alloy from the experimental data comprises:
generating a three-dimensional surface profile function of the laser shock reinforced titanium alloy according to the experimental data, and generating an evaluation reference plane of the laser shock reinforced titanium alloy according to the three-dimensional surface profile function and a preset Gaussian low-pass filter;
and generating the surface roughness of the laser shock reinforced titanium alloy according to the evaluation reference plane and the three-dimensional surface profile function.
7. The method for improving mechanical properties of a titanium alloy based on laser shock peening as defined in claim 1, wherein said generating microhardness values of the laser shock peening titanium alloy according to the experimental data and a preset microhardness algorithm comprises:
acquiring hardness data of a microhardness meter in the experimental data;
generating microhardness values of the laser shock peening titanium alloy using the hardness data and a microhardness algorithm:
wherein H is v Is the microhardness value of the laser shock reinforced titanium alloy, P is the loading load in the hardness data, d is the diagonal length of the impression of the laser shock reinforced titanium alloy surface, and alpha is the included angle of two opposite sides of the diamond pressing head in the hardness data.
8. The method for improving mechanical properties of a titanium alloy based on laser shock peening according to claim 1, wherein said generating a standard curve of said experimental data according to said subject and said mechanical parameters comprises:
establishing a blank coordinate system, and determining coordinate elements of the blank coordinate system according to the theme and the mechanical parameters;
generating discrete points of the blank coordinate system according to the coordinate elements and the experimental data, and determining a theoretical function of a standard curve to be fitted by using the discrete points;
calculating a fitting error value of the experimental data according to the theoretical function and a preset fitting algorithm, and generating a standard curve of the experimental data according to the fitting error value, wherein the preset fitting algorithm is as follows:
wherein L is the fitting error value of the experimental data, y i Is the experimental data, f (x) is the theoretical function, i is the ith data in the experimental data, and m is the total number of data in the experimental data.
9. The method for improving mechanical properties of a titanium alloy based on laser shock peening according to any one of claims 1 to 8, wherein said performing region selection on said standard curve according to a preset interval threshold to obtain a region curve of said standard curve comprises:
determining a target endpoint of the standard curve according to a preset interval threshold value, and determining a target area of the standard curve according to the target endpoint;
and generating a region curve of the standard curve by using the target region and the standard curve.
10. A titanium alloy mechanical property improving device based on laser shock peening, characterized in that the device comprises:
the topic classification module is used for acquiring historical data of the titanium alloy, and performing topic classification on the historical data to obtain topic data of the historical data;
the mechanical parameter module is used for generating experimental data of the laser shock reinforced titanium alloy according to the subject of the subject data and generating mechanical parameters of the laser shock reinforced titanium alloy according to the experimental data;
the region selection module is used for generating a standard curve of the experimental data according to the subject and the mechanical parameter, and performing region selection on the standard curve according to a preset interval threshold value to obtain a region curve of the standard curve;
the sample refining module is used for refining the samples of the regional curve by using a preset interpolation algorithm to obtain refined variables of the regional curve;
and the optimization parameter module is used for generating the optimization parameters of the laser shock reinforced titanium alloy by using the refinement variables, and determining the optimization parameters as the optimal performance improvement parameters of the laser shock reinforced titanium alloy.
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| CN117373580B (en) * | 2023-12-05 | 2024-03-08 | 宝鸡富士特钛业（集团）有限公司 | Performance analysis method and system for realizing titanium alloy product based on time sequence network |
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