CN112861318A - Material constitutive model parameter identification method and system based on cutting imaging - Google Patents
Material constitutive model parameter identification method and system based on cutting imaging Download PDFInfo
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Abstract
The invention belongs to the field of metal cutting processing, and particularly discloses a material constitutive model parameter identification method and system based on cutting imaging, wherein the method comprises the steps of carrying out a quasi-static compression experiment on a workpiece to obtain parameters for representing strain action in a constitutive model; s2, performing a cutting experiment on the workpiece, and obtaining a strain field, a strain rate field and a temperature field based on an imaging method and measuring actual shearing force; s3, calculating theoretical shearing force according to the initial values of parameters representing strain rate and temperature action, the parameters representing strain action and the strain field, the strain rate field and the temperature field in the preset constitutive model, and performing iterative updating on the parameters representing strain rate and temperature action according to the theoretical shearing force and the actual shearing force until the error between the theoretical shearing force and the actual shearing force is smaller than a preset value, thereby completing the parameter identification of the constitutive model. The data of the method are completely derived from real cutting experiments, and the identified constitutive model has accurate parameter results and wide application range.
Description
Technical Field
The invention belongs to the field of metal cutting processing, and particularly relates to a material constitutive model parameter identification method and system based on cutting imaging.
Background
The quality of a metal-cutting formed part is measured by its surface integrity. Surface integrity is a description of The state and properties of a machined surface and its relationship to function and performance, and was initially studied in The beginning of The 20 th century 50 years and received increasing attention in The next decades, and International conference on International Production Engineering for Production Engineering (CIRP) was called for in two years and strict requirements on surface integrity, such as residual stress, after machining of parts are put forward by many enterprises. In recent years, it has been proposed by CIRP front seats that directly affecting the surface integrity are some physical quantities such as strain, strain rate and temperature, etc. in the middle of the cutting process. The physical quantity in the cutting process is generally described by using a constitutive model, and the constitutive model describes stress sigma, strain epsilon and strain rate
Relationship between temperatures T, composition
Determining accurate constitutive parameters is a prerequisite for an accurate description of the cutting process.
Some researchers identify constitutive parameters through some standard material tests, but in the actual cutting process, the strain and strain rate of the material are far higher than the values which can be achieved by the tests; some theoretical cutting models, such as the Oxley cutting analysis model, or the finite element simulation cutting process are used for identification, but the models are simplified for practical situations, and composite materials are increasingly used nowadays, and some material characteristics required to be considered in analysis are not easy to obtain.
As the performance of the camera is more and more excellent, the corresponding Digital Imaging Correlation (DIC) technology is more and more mature. The technology essentially tracks and matches the characteristic points of the pixels on the surface of an object, thereby obtaining the displacement vector field of the surface of the object. Earlier, researchers observed deformation of materials in material mechanics experiments by means of DIC technology, and research on cutting mechanism is now also carried out by DIC. The actual cutting process and the separation process of the chips and the workpiece matrix can be observed through an imaging means, the whole cutting process is more intuitively understood, and the quantities of the shearing angle, the chip-tool contact length and the like which are obtained through complicated model calculation originally can be directly obtained from the graph. After the displacement field is obtained, the strain field and the strain rate field can be further calculated, which are directly obtained in the cutting process and are highly matched with the actual situation.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a material constitutive model parameter identification method and system based on cutting imaging, and aims to obtain strain field, strain rate field, temperature field and actual shear force data through a cutting experiment, calculate theoretical shear force by substituting the strain field, strain rate field and temperature field into a constitutive model, compare the theoretical shear force with the actual shear force, and continuously iterate to complete constitutive model parameter identification, so that the identification parameter result is accurate and the application range is wide.
In order to achieve the above object, according to one aspect of the present invention, a material constitutive model parameter identification method based on cut imaging is provided, including the following steps:
s1, performing a quasi-static compression experiment on a workpiece made of the material to be tested to obtain parameters for representing the strain action in the material constitutive model;
s2, performing a cutting experiment on a workpiece made of a material to be measured to obtain a strain field, a strain rate field, a temperature field and actual shearing force data;
s3, calculating theoretical shearing force according to the preset initial values of parameters representing the strain rate and the temperature action in the constitutive model, the parameters representing the strain action in the constitutive model, and data of a material strain field, a strain rate field and a temperature field to obtain theoretical shearing force, and updating the parameters representing the strain rate and the temperature action in the constitutive model according to the theoretical shearing force and the actual shearing force;
s4, calculating theoretical shearing force according to the parameters representing the strain rate and the temperature action in the updated constitutive model, the parameters representing the strain action in the constitutive model, and the data of the material strain field, the strain rate field and the temperature field to obtain theoretical shearing force, and updating the parameters representing the strain rate and the temperature action in the constitutive model according to the theoretical shearing force and the actual shearing force;
and S5 repeating S4 until the error between the theoretical shearing force and the actual shearing force is smaller than a preset allowable error, wherein the parameters representing the strain rate and the temperature action in the constitutive model are the parameters representing the strain rate and the temperature action in the constitutive model, and the parameter identification of the material constitutive model is completed.
Preferably, in S1, a quasi-static compression experiment is performed on the workpiece made of the material to be measured, so as to obtain a relationship curve between the compressive load and the compressive displacement, and a relationship between the stress and the strain is obtained according to the relationship curve, so as to obtain a parameter representing the strain action in the material constitutive model.
Further preferably, the acquiring strain field, strain rate field, temperature field and actual shear force data in S2 specifically includes the following steps:
s21, cutting a workpiece made of a material to be measured according to preset cutting parameters, synchronously and respectively measuring a cutting force and a temperature field by a dynamometer (5) and an infrared camera (4), solving a corresponding actual shearing force according to the cutting force, continuously shooting two pictures in a cutting process by a double-frame camera (3) according to a preset frame interval, and obtaining a displacement field according to the pictures;
s22, time is built in the infrared camera (4) and the double-frame camera (3), the displacement field and the temperature field at the same time are corresponded, and the corresponding strain field and strain rate field are obtained according to the displacement field, so that strain field, strain rate field, temperature field and actual shearing force data are obtained.
Further preferably, the S2 further includes the following steps: s23, changing cutting parameters, and repeating the steps S21 and S22 for a plurality of times, thereby obtaining a plurality of groups of strain field, strain rate field, temperature field and actual shearing force data.
More preferably, in S21, the two pictures taken by the two-frame camera (3) are processed by a digital image correlation method to obtain the displacement field.
Further preferably, the workpiece made of the material to be measured is preferably sheet-shaped, and the painting treatment is performed on the infrared camera observation surface of the workpiece, and the sand blasting treatment is performed on the double-frame camera observation surface of the workpiece.
More preferably, the cutting parameters include a cutting speed and a feed rate, the cutting speed is 30m/min to 210m/min, and the feed rate is 0.1mm to 0.15 mm.
According to another aspect of the invention, a material constitutive model parameter identification system based on cutting imaging is provided, which comprises a double-frame camera, an infrared camera, a dynamometer, a displacement fine adjustment platform, a displacement coarse adjustment platform and a signal acquisition module, wherein:
the double-frame camera is arranged on the coarse displacement adjusting platform through the fine displacement adjusting platform and is used for shooting a cutting process to obtain data of a strain field and a strain rate field; the infrared camera is arranged on the coarse displacement adjusting platform and is used for acquiring temperature field data; the dynamometer is used for acquiring actual shearing force data; and the signal acquisition module is connected with the double-frame camera, the infrared camera and the dynamometer and is used for collecting data acquired by the double-frame camera, the infrared camera and the dynamometer.
As a further preferred, the system further comprises a laser light source for providing a light source when the two-frame camera takes a picture.
Preferably, the system further comprises a position sensor and a signal synchronous triggering module, wherein the position sensor is used for acquiring the cutting progress of the workpiece and transmitting the cutting progress to the signal synchronous triggering module, and the signal synchronous triggering module controls the double-frame camera, the infrared camera and the dynamometer to work according to the cutting progress.
Generally, compared with the prior art, the above technical solution conceived by the present invention mainly has the following technical advantages:
1. according to the method, the theoretical shearing force is calculated by substituting the strain field, the strain rate field and the temperature field into the constitutive model, the theoretical shearing force is compared with the actual shearing force, and the constitutive model parameter identification is completed through continuous iteration optimization.
2. Compared with the traditional mechanical test, the method directly obtains relevant data through a cutting experiment, and uses the double-frame camera to measure under a high-speed cutting condition, so that the identified constitutive parameters are suitable for a wider range of strain and strain rate and can contain a common cutting condition.
3. The invention processes the pictures acquired by the double-frame camera through a Digital image Correlation method to obtain the displacement field, and the method does not depend on the knowledge of the material, and can also obtain the accurate deformation condition of the strange composite material.
4. The invention makes the workpiece into a sheet shape, carries out paint spraying treatment on the observation surface of the infrared camera to assist thermal imaging, and carries out sand blasting treatment on the observation surface of the double-frame camera to form speckles, thereby facilitating the double-frame camera to calculate the displacement field of the workpiece to be measured according to the displacement of the speckles.
5. Considering the limitation of the camera view field size and the minimum frame interval, the invention controls the cutting speed to be within the range of 30 m/min-210 m/min and the feeding amount to be within the range of 0.1 mm-0.15 mm, so that the camera can acquire a clear picture of the cutting process.
6. The measuring system provided by the invention can realize simultaneous measurement of the cutting force, the temperature field and the displacement field, has a simple structure, is easy to install, can be used on a lathe of a common cutting experiment, and has universality.
Drawings
FIG. 1 is a flowchart of a material constitutive model parameter identification method based on cutting imaging according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a material constitutive model parameter identification system according to an embodiment of the invention;
FIG. 3 is a diagram of an overall entity of the material constitutive model parameter identification system according to the embodiment of the present invention;
FIG. 4 is a diagram of a local entity of the material constitutive model parameter identification system according to the embodiment of the present invention.
The same reference numbers will be used throughout the drawings to refer to the same or like elements or structures, wherein: the method comprises the steps of 1, a signal synchronous triggering module, 2, a signal acquisition module, 3, a double-frame camera, 4, an infrared camera, 5, a dynamometer, 6, a laser light source, 7, a position sensor, 8, a coarse displacement adjusting platform, 9, a fine displacement adjusting platform, 10, a cutter and 11, wherein the workpiece is arranged on a workpiece.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment of the invention provides a material constitutive model parameter identification method based on cutting imaging, which takes a nickel-aluminum bronze material as an object to identify Johnson-Cook (J-C) constitutive model parameters, wherein the J-C model expression is as follows:
the three parts multiplied on the right side of the formula respectively describe strain epsilon and strain rate
And the effect of the temperature T on the stress sigma,
reference strain rate for material, TmIs the melting point of the material, T0The reference temperature (room temperature) is adopted, and parameters to be solved comprise A, B, C, m and n; as shown in fig. 1, the method specifically comprises the following steps:
s1 quasi-static compression experiments identified parameters characterizing strain effects in the constitutive model (A, B and n):
s11 preparation of nickel-aluminum bronze material
The cylindrical piece adopts a Gleebe-3500 material testing machine, and the experimental conditions are set to be 25 ℃ at room temperature and 0.001s in strain rate according to the environment and the material properties-1In order to meet the quasi-static condition, the deformation rate of the test piece is set to be 0.3mm/min, the experiment is repeated for 3 times, and a relation curve between the compression load P and the compression displacement delta L is recorded and output by the experiment machine;
s12 dividing the compressive load by the initial cross-sectional area of the specimen to obtain the engineering stress sigmaeAnd the compressive displacement is divided by the initial length to obtain the engineering strain epsiloneTherefore, a relation curve of stress and strain is obtained through a relation curve between the compression load and the compression displacement; under quasi-static conditions, the strain rate is considered to be approximately 0, the temperature does not change, the two terms after the constitutive model can be ignored, and the strain rate is simplified into the condition that sigma is A + B epsilonnThe constitutive model parameters A, B and n are determined from the stress versus strain curve.
S2 cutting experiment acquires strain field, strain rate field, temperature field and actual shear force data:
s21 assembling the measuring system: by adopting the system shown in fig. 2 to 4, specifically, the displacement coarse adjustment platform 8 is installed on a slide rail of a lathe, the double-frame camera 3 is installed on the displacement coarse adjustment platform 8 through the displacement fine adjustment platform 9, and the infrared camera 4 is installed on the displacement coarse adjustment platform 8; the workpiece 11 and the cutter 10 are arranged on a machine tool, and the position of the cutter point of the cutter 10 extends 10 mm-20 mm out of the edge of a clamp of the cutter 10, so that the cutter point is close to the central line of the double-frame camera 3; the laser light source 6 and the position sensor 7 are clamped through a magnetic base, the magnetic base is fixedly adsorbed on a lathe slide rail, and the position sensor 7 and the tool nose are arranged on two sides of the diameter direction of the workpiece 11 clamp;
s22 pre-experiment adjustment: x, Z (all refer to the direction in the machine tool coordinate system) does not retract after the tool setting is finished; adjusting X, Y directions of the coarse displacement adjusting platform 8 and the fine displacement adjusting platform 9 to enable the middle part of the workpiece 11 and the tool nose of the tool 10 to obtain a good view field in the double-frame camera 3, and adjusting the distance between the tool nose and the double-frame camera 3 in the Z direction to realize focusing of the double-frame camera 3; the incident angle and the position of the laser light source 6 are adjusted to obtain a good illumination effect; according to the position relation between the position sensor 7 and the tool nose of the tool 10, calculating the time from the time when the position sensor 7 senses the workpiece 11 to the time required by the tool 10 to cut the workpiece 11 under the condition of different rotating speeds, and adjusting the time delay setting of the signal synchronous triggering module 1 according to the time so as to ensure that different measuring instruments can accurately and effectively measure the cutting state under the same transient state;
s23 cutting experiment: determining cutting parameters, feeding a cutter in the direction of 10X, rotating a main shaft forward to cut, rotating a workpiece 11 to a sensing area of a position sensor 7, acquiring a signal by the position sensor 7 and transmitting the signal to a signal synchronous triggering module 1, receiving the signal by the signal synchronous triggering module 1, immediately triggering a force measuring instrument 5 and an infrared camera 4 to carry out synchronous measurement, triggering a double-frame camera 3 and a laser light source 6 to take a first picture, and triggering the laser light source 6 to take a second picture again after the time of 3 frame intervals of the double-frame camera; further, in the range of cutting speed of 30-210 m/min and feed quantity of 0.1-0.15 mm, changing cutting parameters, carrying out multiple experimental measurements to obtain multiple groups of data, and repeating the same parameters for more than three times;
specifically, during each experiment, the dynamometer 5 and the infrared camera 4 start measuring when the position sensor 7 senses the workpiece 11, the double-frame camera 3 takes a picture when cutting the middle area close to the workpiece 11, and the laser light source 6 is triggered to provide illumination when the double-frame camera 3 takes a picture twice; the method comprises the following steps that before the infrared camera 4 is used, the reflectivity of a workpiece material is calibrated to accurately measure a temperature field, the dynamometer 5 obtains cutting force, the double-frame camera 3 shoots a cutting process under a mesoscale to obtain two pictures separated by several microseconds, each pixel is about 0.6 micrometer under the condition that a lens is magnified five times, and the double-frame camera 3 preferably adopts a PCO Pixelfy USB camera;
and S24 cutting data processing: for two pictures shot by the double-frame camera 3 in each experiment, processing the pictures by a digital image correlation method to obtain a displacement field, and further obtaining a strain field and a strain rate field according to the displacement field; specifically, (1) two pictures are respectively called as a reference image and a current image, firstly, a seed point is selected in an area with small deformation of the reference image, the nearest whole pixel point is found in the current image as an initial corresponding point according to neighborhood (called as subset) information and a normalized least square criterion, then, the optimal matching point is found through the optimization of a Gaussian-Newton forward iteration algorithm, then, the most matched point is found around the seed point and the corresponding point as a new seed point and the initial corresponding point thereof for optimization, finally, the step is repeated for continuous diffusion, the corresponding points are found in the current image for the points in the reference image, the global matching is completed, and displacement vectors of all pixel points and the corresponding points form a displacement field; (2) according to gradient information of a displacement field, calculating to obtain Green-Lagrangian strain, performing smoothing processing by using a mobile least square plane fitting algorithm to remove errors caused by gradient calculation, calculating equivalent strain by using a Von-Mises theory, calculating to obtain a strain increment at the position, removing a frame interval between two images from the strain increment to obtain a strain rate field, calculating to obtain a streamline field according to the displacement field based on a steady cutting assumption, and integrating the strain increment along a streamline to obtain a strain field;
the infrared camera 4 shoots to obtain a temperature field and a change process in a visual field in an experimental process, the synchronous trigger module sets the time difference of starting working of the infrared camera 4 and the double-frame camera 3, and the temperature field at the corresponding moment when the double-frame camera 3 shoots pictures is found by combining clocks in the two cameras; the dynamometer 5 and the infrared camera 4 perform synchronous measurement to obtain force signals (cutting force) in three directions along a machine tool coordinate system, and the force signals are projected to the shearing direction to obtain actual shearing force, so that a group of strain field, strain rate field, temperature field and actual shearing force data are obtained; and then according to the method, obtaining a plurality of groups of strain fields, strain rate fields, temperature fields and actual shearing force data according to data obtained by a plurality of experiments under different cutting parameters.
S3 identifies parameters characterizing strain rate and temperature effects in the constitutive model (C, m):
s31, presetting initial values of the parameters C and m according to relevant documents; identifying a shear zone in a shear deformation zone according to the strain rate field, calculating stress distribution on the shear zone according to preset parameters C and m, the parameters A, B and n obtained in the step S1, the strain field, the strain rate field and temperature field data by using a constitutive model expression, and integrating the stress along the shear zone direction to obtain the theoretical shear force in the cutting process; updating the parameters C and m by adopting a Gauss-Newton method according to the difference value of the theoretical shearing force and the actual shearing force;
s32, calculating to obtain theoretical shearing force according to the updated parameters C and m, the parameters A, B and n obtained in the step S1 and data of a strain field, a strain rate field and a temperature field, updating the parameters C and m according to the difference value of the theoretical shearing force and the actual shearing force, specifically, substituting a group of data obtained in each experiment into a constitutive model to obtain an equation, obtaining an overconstrained equation set by a plurality of groups of data, and obtaining new C and m through least square fitting calculation;
and S33 repeating S32 until the error between the theoretical shearing force and the actual shearing force is smaller than a preset value, finishing iteration, and finishing the parameter identification of the constitutive model of the material, wherein the parameters C and m are evaluated.
For other constitutive models, the parameters can be obtained by adopting the method in the same way.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A material constitutive model parameter identification method based on cutting imaging is characterized by comprising the following steps:
s1, performing a quasi-static compression experiment on a workpiece made of the material to be tested to obtain parameters for representing the strain action in the material constitutive model;
s2, performing a cutting experiment on a workpiece made of a material to be measured to obtain a strain field, a strain rate field, a temperature field and actual shearing force data;
s3, calculating theoretical shearing force according to the preset initial values of parameters representing the strain rate and the temperature action in the constitutive model, the parameters representing the strain action in the constitutive model, and data of a material strain field, a strain rate field and a temperature field to obtain theoretical shearing force, and updating the parameters representing the strain rate and the temperature action in the constitutive model according to the theoretical shearing force and the actual shearing force;
s4, calculating theoretical shearing force according to the parameters representing the strain rate and the temperature action in the updated constitutive model, the parameters representing the strain action in the constitutive model, and the data of the material strain field, the strain rate field and the temperature field to obtain theoretical shearing force, and updating the parameters representing the strain rate and the temperature action in the constitutive model according to the theoretical shearing force and the actual shearing force;
and S5 repeating S4 until the error between the theoretical shearing force and the actual shearing force is smaller than a preset allowable error, wherein the parameters representing the strain rate and the temperature action in the constitutive model are the parameters representing the strain rate and the temperature action in the constitutive model, and the parameter identification of the material constitutive model is completed.
2. The method for identifying parameters of a material constitutive model based on cutting imaging as claimed in claim 1, wherein in S1, a quasi-static compression experiment is performed on a workpiece made of a material to be tested to obtain a relation curve between a compression load and a compression displacement, and a relation between stress and strain is obtained according to the relation curve to obtain parameters representing strain action in the material constitutive model.
3. The method for identifying parameters of a material constitutive model based on cutting imaging as claimed in claim 1, wherein the obtaining of the strain field, the strain rate field, the temperature field and the actual shear force data in S2 includes the following steps:
s21, cutting a workpiece made of a material to be measured according to preset cutting parameters, synchronously and respectively measuring a cutting force and a temperature field by a dynamometer (5) and an infrared camera (4), solving a corresponding actual shearing force according to the cutting force, continuously shooting two pictures in a cutting process by a double-frame camera (3) according to a preset frame interval, and obtaining a displacement field according to the pictures;
s22, time is built in the infrared camera (4) and the double-frame camera (3), the displacement field and the temperature field at the same time are corresponded, and the corresponding strain field and strain rate field are obtained according to the displacement field, so that strain field, strain rate field, temperature field and actual shearing force data are obtained.
4. The method for identifying parameters of a material constitutive model based on cut imaging as claimed in claim 3, wherein the step of S2 further comprises the steps of: s23, changing cutting parameters, and repeating the steps S21 and S22 for a plurality of times, thereby obtaining a plurality of groups of strain field, strain rate field, temperature field and actual shearing force data.
5. The method for identifying material constitutive model parameters based on ablation imaging as claimed in claim 3, wherein in the step S21, the displacement field is obtained by processing two pictures taken by the two-frame camera (3) through a digital image correlation method.
6. The material constitutive model parameter identification method based on cutting imaging as claimed in claim 3, wherein the workpiece made of the material to be measured is preferably sheet-shaped, and is painted on the infrared camera (4) observation surface of the workpiece, and is sandblasted on the double-frame camera (3) observation surface of the workpiece.
7. The material constitutive model parameter identification method based on cutting imaging as claimed in any one of claims 1 to 6, wherein the cutting parameters comprise cutting speed and feed amount, the cutting speed is 30m/min to 210m/min, and the feed amount is 0.1mm to 0.15 mm.
8. Material texture model parameter identification system for implementing the method according to any one of claims 1 to 7, comprising a two-frame camera (3), an infrared camera (4), a force gauge (5), a fine displacement platform (9), a coarse displacement platform (8) and a signal acquisition module (2), wherein:
the double-frame camera (3) is arranged on the coarse displacement adjusting platform (8) through the fine displacement adjusting platform (9) and is used for shooting a cutting process to acquire data of a strain field and a strain rate field; the infrared camera (4) is arranged on the coarse displacement adjusting platform (8) and is used for acquiring temperature field data; the dynamometer (5) is used for acquiring actual shearing force data; the signal acquisition module (2) is connected with the double-frame camera (3), the infrared camera (4) and the dynamometer (5) and is used for collecting data acquired by the double-frame camera (3), the infrared camera (4) and the dynamometer (5).
9. The material constitutive model parameter identification system of claim 8, further comprising a laser light source (6), wherein the laser light source (6) is used for providing a light source when the two-frame camera (3) shoots.
10. The material constitutive model parameter identification system of claim 8, further comprising a position sensor (7) and a signal synchronous trigger module (1), wherein the position sensor (7) is used for acquiring a cutting progress of a workpiece and transmitting the cutting progress to the signal synchronous trigger module (1), and the signal synchronous trigger module (1) controls the double-frame camera (3), the infrared camera (4) and the force measuring instrument (5) to work according to the cutting progress.
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| CN117095773A (en) * | 2023-03-21 | 2023-11-21 | 哈尔滨理工大学 | Method for establishing right-angle cutting equal-divided shearing area model characterization based on Oxley theory |
| CN117095773B (en) * | 2023-03-21 | 2024-04-05 | 哈尔滨理工大学 | Method for establishing right-angle cutting equal-divided shearing area model characterization based on Oxley theory |
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