CN107657129B - Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring - Google Patents
Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring Download PDFInfo
- Publication number
- CN107657129B CN107657129B CN201710964936.XA CN201710964936A CN107657129B CN 107657129 B CN107657129 B CN 107657129B CN 201710964936 A CN201710964936 A CN 201710964936A CN 107657129 B CN107657129 B CN 107657129B
- Authority
- CN
- China
- Prior art keywords
- residual stress
- sensing
- clamping force
- stress deformation
- deformation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The invention discloses a thin-wall part residual stress deformation perception prediction method based on clamping force monitoring, which is used for solving the technical problem of poor practicability of the existing thin-wall part residual stress deformation prediction method. The technical scheme includes that firstly, the residual stress deformation tendency of a thin-wall part is estimated through a finite element simulation method, and clamping force sensing points are added in a large deformation area; then designing a sensing clamp, and monitoring the change of clamping force in the machining process at a sensing point through a pressure sensor; and finally, by establishing a finite element model of the static fixed base of the clamping system and applying the counter force of the change value of the clamping force at the sensing point, the residual stress deformation of the part is obtained, and the prediction of the residual stress deformation of the thin-wall part is realized. The method does not need to obtain an accurate machining residual stress value, solves the technical problem of large deformation prediction error caused by inaccurate machining residual stress applied by the existing thin-wall part residual stress deformation prediction method, simultaneously solves the technical problem that the residual stress deformation of the thin-wall part is difficult to predict accurately, and has good practicability.
Description
Technical Field
The invention relates to a thin-wall part residual stress deformation prediction method, in particular to a thin-wall part residual stress deformation perception prediction method based on clamping force monitoring.
Background
Finite element simulation is the current main research method for predicting residual stress deformation. The method commonly adopted for simulating the residual stress deformation at present is as follows: aiming at the initial residual stress deformation, applying the measured initial residual stress of the blank to a finite element model of the blank, and simulating the removal of materials by using a unit life and death method to obtain the structure and the stress distribution state of the final part so as to obtain the initial residual stress deformation; aiming at the machining residual stress deformation, a method of applying the residual stress distribution of the machining surface layer obtained by X-ray diffraction measurement under a certain fixed working condition to the surface layer of the part is mostly adopted, and the machining residual stress deformation is obtained by stress balance.
The document "finish Element Modeling of Part diagnosis, ICIRA 2008, Part II, LNAI 5315, pp.329-338,2008" discloses a method for predicting residual stress deformation of a thin-wall Part. The method adopts a finite element simulation technology, applies the initial residual stress of the measured blank material and the processing residual stress of the surface of the part to a finite element model of the part, realizes material removal through simulating the cutting process of a cutter, and finally predicts and obtains the residual stress deformation of the part.
The application of the method has great limitation, and the method can only carry out simulation research on the ideal machining state of parts with simple working conditions and simple part structures, and has larger difference from actual machining. In actual processing, due to the influence of factors such as cutter abrasion and uneven material distribution, the distribution of processing residual stress under the same fixed working condition is inconsistent, so that the stress application is inaccurate; in addition, the complex profile structure and the time-varying processing condition of most thin-wall parts also cause that the residual stress is difficult to accurately obtain, and the residual stress deformation cannot be accurately predicted by adopting a finite element simulation method.
Disclosure of Invention
In order to overcome the defect that the existing thin-wall part residual stress deformation prediction method is poor in practicability, the invention provides a thin-wall part residual stress deformation perception prediction method based on clamping force monitoring. The method comprises the steps of firstly, estimating the residual stress deformation tendency of a thin-wall part by a finite element simulation method, and adding a clamping force sensing point in a large deformation area; then designing a sensing clamp, and monitoring the change of clamping force in the machining process at a sensing point through a pressure sensor; and finally, by establishing a finite element model of the static fixed base of the clamping system and applying the counter force of the change value of the clamping force at the sensing point, the residual stress deformation of the part is obtained, and the prediction of the residual stress deformation of the thin-wall part is realized. The method does not need to obtain an accurate machining residual stress value, and solves the technical problem of large deformation prediction error caused by inaccurate machining residual stress applied by the existing thin-wall part residual stress deformation prediction method. The sensing monitoring technology is applied to the thin-wall part machining, so that the problem that the residual stress deformation of the thin-wall part is difficult to accurately predict is solved, and the practicability is good.
The technical scheme adopted by the invention for solving the technical problems is as follows: a thin-wall part residual stress deformation perception prediction method based on clamping force monitoring is characterized by comprising the following steps:
step one, determining a clamping force sensing position. In finite element analysis software, a three-dimensional model of a part is established, material properties and boundary conditions are given to the established finite element model, the model is divided into grids so as to obtain a plurality of units, an approximate machining residual stress distribution is applied to surface layer units according to the depth from a machining surface, finite element analysis is submitted, and the deformation state of the part is estimated. And applying a clamping force sensing point at a position with larger deformation.
And step two, designing a clamping scheme. A special sensing clamp is designed, redundant constraint is designed into a point constraint type for sensing clamping force conveniently, and a pressure sensor is installed on the point constraint clamp.
Step three, processing and sensing. And (5) clamping the part according to the clamping scheme designed in the step two, and finishing the machining of the part according to the given working condition. The value of the clamping force is recorded at a set sensing time point.
And step four, solving the residual stress deformation.
(a) And establishing a mathematical model for perception and prediction of residual stress deformation.
The mathematical model for perceptual prediction is expressed as follows:
S＝f(ΔE) (1)
where Δ E is the perceptual vector: clamping force variation values at different sensing positions (1-n) at different sensing moments (1-m). Defining an initial clamping force as E0＝[e01 e02 … e0n]And each element represents the clamping force of sensing positions 1-n at the initial moment 0, wherein the numerical value of each element needs to be determined through sensing of the sensor. The processing process of the part is equivalent to providing excitation for a sensing system to change the clamping force, and the clamping force at the moment 1 is defined as E1＝[e11 e12 … e1n]Then clamping force variation vector Delta E1＝E1-E0With the cutting process, the new sensing time is determined, and the sensed clamping force is respectively E2 E3 … EmThe correspondingly expanded clamping force variation vectors are respectively delta E2 ΔE3 … ΔEmThe sensing vector of the whole cutting process is delta E ═ delta E1 ΔE2 … ΔEm]T. Example perceptionThe vector is a change value of clamping force of the sensing point position determined in the step (a) before and after processing.
S is a perceptual prediction target vector: and (3) residual stress deformation vectors of the parts at different sensing positions (1-n) at different sensing moments (1-m). Target vector S ═ S1 S2 … Sm]TAnd each element represents the residual stress deformation of the part at different sensing moments, namely the residual stress deformation of different positions of the clamping part is released at different sensing moments. Wherein Si＝[Si1 Si2 … Sin]Representing the residual stress deformation values of different positions of the part at the ith sensing moment, and it should be noted that the value positions of all elements do not necessarily correspond to the sensing positions. Embodiments perceive the predicted target vector as a residual stress deformation vector of the part along a line in the length.
And f, delta E → S is the mapping relation from the perception vector to the target vector. The mapping relation solves the target vector through the sensing vector, and therefore the sensing prediction of the residual stress deformation is achieved. The mapping relation is obtained by theoretical derivation, finite element simulation or intelligent algorithm means. Embodiments use finite element simulation to obtain this mapping.
(b) And (5) solving the perception prediction model.
For the solution of the residual stress deformation perception of the hyperstatic clamping system for N times, the following deformation coordination equations are provided at different redundant constraint points:
in the formula:
eirepresenting a change in the restraining force on each redundant restraint;
δij(i ═ 1,2,3 …, n; (j;) 1,2,3 …, n;) represents statically determinate structure at ejWhen acting alone, edge eiDisplacement of direction;
ΔiMrepresenting statically determinate structure under the action of residual stress aloneiDisplacement of direction;
therefore, a solving formula of the hyperstatic clamping structure perception model for N times is obtained:
ΔM＝-δe (3)
in the formula:
and (3) the residual stress deformation after the part is clamped and unloaded is equal to the deformation caused by the counter force of the change value of the clamping force of the sensing point acting on the part alone, and the deformation state of the part is obtained. The deformation state at this time is the residual stress deformation value after the part is clamped and unloaded.
The invention has the beneficial effects that: the method comprises the steps of firstly, estimating the residual stress deformation tendency of a thin-wall part by a finite element simulation method, and adding a clamping force sensing point in a large deformation area; then designing a sensing clamp, and monitoring the change of clamping force in the machining process at a sensing point through a pressure sensor; and finally, by establishing a finite element model of the static fixed base of the clamping system and applying the counter force of the change value of the clamping force at the sensing point, the residual stress deformation of the part is obtained, and the prediction of the residual stress deformation of the thin-wall part is realized. The method does not need to obtain an accurate machining residual stress value, and solves the technical problem of large deformation prediction error caused by inaccurate machining residual stress applied by the existing thin-wall part residual stress deformation prediction method. The sensing monitoring technology is applied to the thin-wall part machining, so that the problem that the residual stress deformation of the thin-wall part is difficult to accurately predict is solved, and the practicability is good.
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Drawings
FIG. 1 is a comparison graph of a prediction result and an actual measurement result in an embodiment of the thin-wall part residual stress deformation perception prediction method based on clamping force monitoring.
Detailed Description
Refer to fig. 1. The embodiment is used for perceiving and predicting the residual stress deformation of the thin plate after the part is clamped and unloaded in the single-side machining process. The sheet blank material is GH4169, the size is 160 × 20 × 2mm, the surface of the middle area is processed by 80 × 20mm, the processing depth is 0.5mm, and areas of 40 × 20mm are reserved at two ends for clamping. The thin plate is subjected to stress relief heat treatment before machining, and residual stress deformation is mainly caused by the introduction of surface machining residual stress.
The thin-wall part residual stress deformation perception prediction method based on clamping force monitoring comprises the following specific steps:
step 1 is implemented: and determining the clamping force sensing position.
In order to determine the sensing position, a machining residual stress deformation prediction analysis finite element model of a static fixed base of a sheet clamping system is established in Abaqus software, and the process is as follows:
establishing a model and setting a foundation: and establishing a three-dimensional model of the thin plate, and dividing the surface layer of the processing surface of the thin plate into 7 layers, wherein each layer is 15um, and the layer is an action area of processing residual stress. Setting a thin plate material as GH4169, fixedly constraining one end of the thin plate, dividing grids by 8-node hexahedron reduction integral entity units C3D8R, and dispersing parts into 192000 units;
TABLE 1 distribution of residual stress of machined surface
Application of residual stress: the residual stress profile shown in table 1 was applied to each layer in depth. The residual stress is measured by X-ray diffraction after milling a GH4169 material block by using the parameters used in the experiment. SigmaXXResidual stress, σ, in the direction of feed speed for the work surfaceYYIs the residual stress of the machined surface perpendicular to the feed direction. If variable working condition machining is adopted, because the cutting residual stress of the fixed cutter in a certain working condition range has similar distribution characteristics, the residual stress distribution under a certain parameter in the working condition range can be applied to the machining surface layer for evaluating the maximum deformation position;
calculating residual stress deformation and post-processing: and obtaining a deformation cloud picture after milling the part according to the finite element calculation result, obtaining the residual stress deformation state of the part under static clamping through a finite element model, and knowing that the single-side processing of the sheet part integrally presents bending deformation, and the maximum deformation position is positioned at the length boundary of the part. The sensing point is set at the midpoint of the width of 10mm from the boundary, taking into account practical clamping constraints.
Step 2 is implemented: and designing a clamping scheme.
The clamp adopts a mode that a pressing plate at one end of a flat plate is used for clamping, and the point-to-point clamping is carried out at one end of the flat plate. The point-to-point ends are respectively provided with a clamping force sensor in a vertically opposite mode, and the contact surface of the sensor and the part is in point contact through an arc surface. The clamp force sensor parameters used were as follows: the range is 0-1000N, and the sensitivity is 1.0 mv/V. In order to ensure the accurate positioning of the point-to-point position, three threaded positioning holes are respectively arranged at corresponding positions on the upper clamp part and the lower clamp part, and the accuracy of the mounting position of the sensor is ensured together with threaded holes on the sensor. In addition, the upper clamp part and the lower clamp part are assembled in a nesting mode, and point-to-point clamping is ensured.
Step 3 is implemented: and (6) processing perception.
The experiment was performed on a YH850 numerically controlled machining center using a two-tooth flat bottom milling cutter. The cutting depth is 0.5mm, the cutting width is 2mm, and the cutting speed is 80 m/min. And a high-precision display instrument is adopted to obtain the numerical value of the clamping force. The sensor sensing value of the upper part of the clamp is 31.6N and the sensor sensing value of the lower part of the clamp is 32.8N, which are obtained by a display instrument before processing. After processing, the upper sensor sensing value is 30.8N, and the lower sensor sensing value is 34.6N.
And (4) implementing the step: and solving the residual stress deformation.
Solving the residual stress deformation of the thin-wall part by the following steps:
(a) and establishing a mathematical model for perception and prediction of residual stress deformation.
The mathematical model of perceptual prediction is expressed in the form:
S＝f(ΔE) (1)
where Δ E is the perceptual vector: clamping force variation values at different sensing positions (1-n) at different sensing moments (1-m). Defining an initial clamping force as E0＝[e01 e02 … e0n]And each element represents the clamping force of sensing positions 1-n at the initial moment 0, wherein the numerical value of each element needs to be determined through sensing of the sensor. The processing process of the parts is equivalent to that of the sensing systemFor energizing to change the clamping force, defining the clamping force at time 1 as E1＝[e11 e12 … e1n]Then clamping force variation vector Delta E1＝E1-E0With the cutting process, the new sensing time is determined, and the sensed clamping force is respectively E2 E3 … EmThe correspondingly expanded clamping force variation vectors are respectively delta E2 ΔE3 … ΔEmThe sensing vector of the whole cutting process is delta E ═ delta E1 ΔE2 … ΔEm]T. The embodiment sensing vector is a change value of clamping force of the position of the sensing point determined in the step 1 before and after processing.
S is a perceptual prediction target vector: and (3) residual stress deformation vectors of the parts at different sensing positions (1-n) at different sensing moments (1-m). Target vector S ═ S1 S2 … Sm]TAnd each element represents the residual stress deformation of the part at different sensing moments, namely the residual stress deformation of different positions of the clamping part is released at different sensing moments. Wherein Si＝[Si1 Si2 … Sin]Representing the residual stress deformation values of different positions of the part at the ith sensing moment, and it should be noted that the value positions of all elements do not necessarily correspond to the sensing positions. Embodiments perceive the predicted target vector as a residual stress deformation vector of the part along a line in the length.
And f, delta E → S is the mapping relation from the perception vector to the target vector. The mapping relation solves the target vector through the sensing vector, and therefore the sensing prediction of the residual stress deformation is achieved. The mapping relation is obtained by theoretical derivation, finite element simulation or intelligent algorithm means. Embodiments use finite element simulation to obtain this mapping.
(b) And (5) solving the perception prediction model.
For the solution of the residual stress deformation perception of the hyperstatic clamping system for N times, the following deformation coordination equations are provided at different redundant constraint points:
in the formula:
eirepresenting a change in the restraining force on each redundant restraint;
δij(i ═ 1,2,3 …, n; (j;) 1,2,3 …, n;) represents statically determinate structure at ejWhen acting alone, edge eiDisplacement of direction;
ΔiMrepresenting statically determinate structure under the action of residual stress aloneiDisplacement of direction;
therefore, a solving formula of the hyperstatic clamping structure perception model for N times is obtained:
ΔM＝-δe (3)
in the formula:
namely, the residual stress deformation after the part is clamped and unloaded is equal to the deformation caused by the action of the counter force of the change value of the clamping force of the sensing point on the part alone. The embodiment is a 2-time hyperstatic clamping system and is suitable for the solving method.
As can be seen from solving equation (3), the residual stress deformation of the thin plate member is equivalent to a deformation value resulting from a load of 2.6N being applied downward on the part. Establishing a finite element simulation model in Abaqus, setting a sheet material to be GH4169, fixedly constraining one end of the sheet, dividing grids by adopting 8-node hexahedron reduction integral entity units C3D8R, and dispersing parts into 192000 units; a deformation cloud of the part is obtained by applying a downward load of 2.6N at the sensing point, and deformation values along the length center line are extracted. And after the machining is finished, unloading the sensing end for clamping, and measuring the deformation of the part along the length center line direction by using deformation measuring equipment.
As can be seen from the comparison between the perception prediction result and the actual measurement result in FIG. 1, the actual measurement maximum deformation is 1.07mm, the perception maximum deformation is 0.93mm, and the maximum perception prediction error is 13%, while the error of the existing residual stress deformation finite element prediction method is about 30%, and the perception prediction obtains a relatively accurate result.
Claims (1)
1. A thin-wall part residual stress deformation perception prediction method based on clamping force monitoring is characterized by comprising the following steps:
step one, determining a clamping force sensing position; establishing a finite element model of the part in finite element analysis software, endowing the established finite element model with material properties and boundary conditions, meshing the finite element model to obtain a plurality of units, applying approximate processing residual stress distribution on surface layer units according to the depth from a processing surface, submitting finite element analysis, and estimating the deformation state of the part; applying a clamping force sensing point at a position with larger deformation;
step two, designing a clamping scheme; designing a special sensing clamp, designing redundant constraint into a point constraint type for facilitating sensing of clamping force, and installing a pressure sensor on the point constraint clamp;
step three, processing perception; clamping the part according to the clamping scheme designed in the step two, and finishing the machining of the part according to the given working condition; recording the numerical value of the clamping force at a set sensing time point;
step four, solving the residual stress deformation;
(a) establishing a mathematical model for sensing and predicting residual stress deformation;
the mathematical model for perceptual prediction is expressed as follows:
S＝f(ΔE) (1)
where Δ E is the perceptual vector: clamping force change values of 1-n at different sensing positions from 1-m at different sensing moments; defining an initial clamping force as E0＝[e01 e02 … e0n]Each element represents the clamping force of sensing positions 1-n at the initial moment 0, wherein the numerical value of each element needs to be determined through sensing of a sensor; the processing process of the part is equivalent to providing excitation for a sensing system to change the clamping force, and the clamping force at the moment 1 is defined as E1＝[e11 e12 … e1n]Then clamping force variation vector Delta E1＝E1-E0With the cutting process, the new sensing time is determined, and the sensed clamping force is respectively E2，E3，…，EmThe correspondingly expanded clamping force variation vectors are respectively delta E2，ΔE3，…，ΔEmThe sensing vector of the whole cutting process is delta E ═ delta E1 ΔE2… ΔEm]T；
S is a perceptual prediction target vector: residual stress deformation vectors of parts 1-n at different sensing positions 1-m at different sensing moments; target vector S ═ S1 S2 … Sm]TEach element represents the residual stress deformation of the part at different sensing moments, namely the residual stress deformation of different positions of the clamping part is released at different sensing moments; wherein Si＝[Si1 Si2 … Sin]Representing the residual stress deformation values of different positions of the part at the ith sensing moment, and it is noted that the value positions of all elements do not necessarily correspond to the sensing positions;
delta E → S is the mapping relation from the perception vector to the target vector; the mapping relation solves a target vector through a sensing vector, so that the sensing prediction of the residual stress deformation is realized; the mapping relation is obtained by theoretical derivation, finite element simulation or intelligent algorithm means;
(b) solving a perception prediction model;
for the solution of the residual stress deformation perception of the hyperstatic clamping system for N times, the following deformation coordination equations are provided at different redundant constraint points:
in the formula:
eirepresenting a change in the restraining force on each redundant restraint;
δiji ═ 1,2,3 …, n; j is 1,2,3 …, n; represents a statically determinate structure in ejWhen acting alone, edge eiDisplacement of direction;
ΔiMrepresenting statically determinate structure under the action of residual stress aloneiDisplacement of direction;
therefore, a solving formula of the hyperstatic clamping structure perception model for N times is obtained:
ΔM＝-δe (3)
in the formula:
ΔM＝[Δ1M Δ2M ΔnM]T；e＝[e1 e2 … en]；
the residual stress deformation after the part clamping and unloading is equal to the deformation caused by the independent action of the counter force of the change value of the clamping force of the sensing point on the part, and the deformation state of the part is obtained; the deformation state at this time is the residual stress deformation value after the part is clamped and unloaded.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710964936.XA CN107657129B (en) | 2017-10-17 | 2017-10-17 | Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710964936.XA CN107657129B (en) | 2017-10-17 | 2017-10-17 | Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107657129A CN107657129A (en) | 2018-02-02 |
| CN107657129B true CN107657129B (en) | 2019-12-20 |
Family
ID=61118438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710964936.XA Active CN107657129B (en) | 2017-10-17 | 2017-10-17 | Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107657129B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109635365A (en) * | 2018-11-22 | 2019-04-16 | 中国航发沈阳黎明航空发动机有限责任公司 | A kind of process of control casing cutting parts deformation |
| CN109765841A (en) * | 2019-01-09 | 2019-05-17 | 西北工业大学 | The space-time mapping method of online monitoring data and part Working position |
| CN110695725B (en) * | 2019-09-09 | 2021-05-14 | 北京航空航天大学 | Aviation thin-wall part tool and using method thereof |
| CN110919459B (en) * | 2019-12-06 | 2020-10-16 | 沈阳航空航天大学 | Method for detecting influence of clamping force on machining deformation of thin-wall part |
| CN111880477B (en) * | 2020-07-30 | 2022-02-11 | 南京航空航天大学 | Machining deformation prediction method integrating mechanism model and learning model |
| CN112014016B (en) * | 2020-07-30 | 2022-02-11 | 南京航空航天大学 | Method and device for accurately measuring deformation force in part machining process |
| CN112926152B (en) * | 2021-02-15 | 2023-04-28 | 西北工业大学 | Digital twin-driven thin-wall part clamping force precise control and optimization method |
| CN114139310A (en) * | 2021-11-25 | 2022-03-04 | 成都飞机工业（集团）有限责任公司 | Deformation prediction and control method for machining reverse-pulling scheme |
| CN116992778B (en) * | 2023-08-30 | 2024-04-26 | 西北工业大学 | Milling residual stress deformation prediction method, storage medium and electronic equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS58100907A (en) * | 1981-12-11 | 1983-06-15 | Hitachi Ltd | Controlling method of sheet gauge in hot rolling mill |
| CN101887472A (en) * | 2009-05-12 | 2010-11-17 | 通用汽车环球科技运作公司 | The method of unrelieved stress and distortion in the prediction quenching aluminium casting |
| CN104111625A (en) * | 2014-08-22 | 2014-10-22 | 南京航空航天大学 | Active machining method for clamping deformation of thin-walled special-shaped workpieces |
| CN104298818A (en) * | 2014-09-26 | 2015-01-21 | 北京理工大学 | Method for predicting and simulating errors of end-milled surface |
| CN105302970A (en) * | 2015-11-04 | 2016-02-03 | 沈阳黎明航空发动机(集团)有限责任公司 | Prediction method of residual stress-redistribution process of thin-walled aviation part |
| CN106529053A (en) * | 2016-11-16 | 2017-03-22 | 西北工业大学 | Method for predicting milling residual stress field of titanium alloy |
| CN106840877A (en) * | 2017-01-22 | 2017-06-13 | 北京工业大学 | A kind of multiaxis crackle total life prediction method based on stress |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012206824A (en) * | 2011-03-29 | 2012-10-25 | Fuji Xerox Co Ltd | Internal residual stress calculating device, and program |
-
2017
- 2017-10-17 CN CN201710964936.XA patent/CN107657129B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS58100907A (en) * | 1981-12-11 | 1983-06-15 | Hitachi Ltd | Controlling method of sheet gauge in hot rolling mill |
| CN101887472A (en) * | 2009-05-12 | 2010-11-17 | 通用汽车环球科技运作公司 | The method of unrelieved stress and distortion in the prediction quenching aluminium casting |
| CN104111625A (en) * | 2014-08-22 | 2014-10-22 | 南京航空航天大学 | Active machining method for clamping deformation of thin-walled special-shaped workpieces |
| CN104298818A (en) * | 2014-09-26 | 2015-01-21 | 北京理工大学 | Method for predicting and simulating errors of end-milled surface |
| CN105302970A (en) * | 2015-11-04 | 2016-02-03 | 沈阳黎明航空发动机(集团)有限责任公司 | Prediction method of residual stress-redistribution process of thin-walled aviation part |
| CN106529053A (en) * | 2016-11-16 | 2017-03-22 | 西北工业大学 | Method for predicting milling residual stress field of titanium alloy |
| CN106840877A (en) * | 2017-01-22 | 2017-06-13 | 北京工业大学 | A kind of multiaxis crackle total life prediction method based on stress |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107657129A (en) | 2018-02-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107657129B (en) | Thin-wall part residual stress deformation perception prediction method based on clamping force monitoring | |
| Plaza et al. | Surface roughness monitoring by singular spectrum analysis of vibration signals | |
| CN102854841B (en) | Shape and position error in-situ compensating and processing method for curved surface parts | |
| Aerens et al. | Force prediction for single point incremental forming deduced from experimental and FEM observations | |
| US7870792B2 (en) | Forming limit strain analysis | |
| US9921572B2 (en) | Springback compensation in formed sheet metal parts | |
| Denkena et al. | Feeling machines for online detection and compensation of tool deflection in milling | |
| Du et al. | Peripheral milling force induced error compensation using analytical force model and APDL deformation calculation | |
| CN105893760B (en) | Tool wear evaluation and prediction technique and system based on broad sense abrasion loss | |
| KR20130037492A (en) | Method for predicting development of curved plates | |
| Cerutti et al. | Prediction of machining quality due to the initial residual stress redistribution of aerospace structural parts made of low-density aluminium alloy rolled plates | |
| CN104298171A (en) | Mesoscale part machining error prediction and control method | |
| IL273294B2 (en) | Metrology method and system | |
| CN105180886B (en) | A kind of method for measuring cold-reduced sheet Strain Distribution | |
| Wang et al. | FEM-based simulation for workpiece deformation in thin-wall milling | |
| CN103213068B (en) | Measuring method for obtaining workpiece edge removal function in ultra-precision gasbag polishing technique | |
| CN104655496B (en) | The method of testing conducted oneself with dignity on the influence of off axis reflector mirror surface-shaped | |
| Zhang et al. | Modeling of tool wear for ball end milling cutter based on shape mapping | |
| Laifa et al. | Evaluation of machining process by integrating 3D manufacturing dispersions, functional constraints, and the concept of small displacement torsors | |
| Raju et al. | Curvelet transform for estimation of machining performance | |
| Marusich et al. | Finite element modeling of part distortion | |
| Firat et al. | A FE technique to improve the accuracy of drawbead models and verification with channel drawing experiments of a high-strength steel | |
| KR101246185B1 (en) | Completion assessment method of curved plates in manufacturing process and system using the same | |
| CN109492323B (en) | High-precision inverse calculation method for initial residual stress of blank based on deformation test | |
| Zeng et al. | On-Machine Estimation of Workholding State for Thin-Walled Parts |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |