CN103439917A - Cutting force prediction method based on features - Google Patents

Abstract

A cutting force prediction method based on features is characterized in that feature recognition is carried out on a part based on a CAD three-dimensional model, and drive geometry recognizing the features is extracted according to a feature recognition result and is dispersed into some points. A primary process decision is carried out to obtain rotating speed, feeding, cutting depth, cutting width and other process parameters, a shearing force action coefficient and a cutting edge force coefficient are measured through experiments, a cut-in angle and a cut-out angle are calculated according to cutting parameters, and finally cutting force is calculated. According to cutting force prediction based on the features, the cutting force can be calculated according to the cutting parameter with different features in the part process decision process, and warning and process modification are carried out on the relatively large feature of the cutting force. Before post-processing, the cutting force can be predicted earlier. The predicted cutting force aims at each feature, that is, the modification is for a single feature, the processing efficiency of each feature of a plane structural component can be maximized, overall efficiency is accordingly maximized, and the number of simulation times is reduced.

Description

Prediction of Turning Force with Artificial method based on feature

Technical field

The present invention relates to a kind of CNC processing technology, especially a kind of Forecasting Methodology of cutting force, the specifically a kind of prediction of Turning Force with Artificial method of type in aircraft structure cavity feature based on feature.

Background technology

Aircraft structure has the characteristics such as size is large, machining precision is high, complex structure.In processing aircraft structure process, local feature can be optimized not due to cutting parameter, makes the excessive feature distortion that causes of local cutting force, and final part is scrapped.Therefore need suitable prediction of Turning Force with Artificial in the aircraft structure first being processed.The prediction of Turning Force with Artificial method mainly contains prediction of Turning Force with Artificial, the prediction of Turning Force with Artificial based on least square method, the prediction of Turning Force with Artificial based on analytical method and the limited element analysis technique based on neural network at present.

Prediction of Turning Force with Artificial based on neural network, need enough samples to train, and forecasting process has no idea to consider actual processing situation, and the cutting force doped is mostly average cutting force, and error is larger; Prediction of Turning Force with Artificial based on least square method, the accuracy of prediction depends primarily on the model of cutting force, utilizes linear regression to obtain by experiment index or the coefficient of cutting Force Model.This Forecasting Methodology is in certain section interval, and the prediction meeting in the definite situation of part material, lathe model, cutter is more accurate.Finite element method prediction cutting force, mostly for predicting static cutting force, accuracy can not guarantee, and prediction dynamic cutting force time-consuming very, can't guaranteed efficiency.

Utilize analytical method prediction cutting force, consider the cutter rotation, the cutting force that blade and part contact area real-time change are brought changes, and can predict dynamic cutting force by the method for infinitesimal analysis, and accuracy rate is higher, is a kind of comparatively many methods of application at present.

Although prediction cutting force mode has a lot, most of prediction of Turning Force with Artificial method all depends on artificial input cutting parameter, lathe information and tool-information, with this, calculates cutting force.Seldom have in conjunction with signatures to predict cutting force, at present newer scientific research is a kind of cavity feature prediction of Turning Force with Artificial based on G code that the people such as Zhao-cheng proposes, although consider feature, but the prediction of Turning Force with Artificial based on G code, to pass through Tool-path Generation, obtain could predicting cutting force after coordinate points after emulation, affect efficiency.

Summary of the invention

The objective of the invention is or inefficient problem not high for existing prediction of Turning Force with Artificial method accuracy when large aircraft trench structure part is predicted, invent a kind of prediction of Turning Force with Artificial method based on feature that can quick and precisely predict cutting force.

Technical scheme of the present invention is:

A kind of Forecasting Methodology of the cutting force based on feature is characterized in that it comprises the following steps:

Step 1, guiding structure part model, carry out feature identification;

Step 2, according to the feature recognition result, obtain machining area, extract and be used for the driving geological information of Tool-path Generation;

Step 3, the process decision of carrying out obtain tool-information, lathe information, technique information, and definite cutting parameter information; Tool-information comprises that cutter material, cutter sword count N and tool diameter R, and the lathe packets of information is containing the lathe model, and the cutting parameter packets of information is containing cutting-in a _p, cut wide a _e, rotation speed n, feeding f;

The feed angle of step 4, each position of calculated characteristics with cut out angle;

Step 5, by trial cut, measure shearing force tangentially, radially and axial function coefficient K _{t τ}, K _{r τ}, K _{a τ}, measure cutting edge force coefficient K simultaneously _{t σ}, K _{r σ}, K _{a σ};

Step 6, by the function coefficient of gained and cutting edge force coefficient substitution cutting force formula, calculate cutting force according to technique information;

The cutting force that step 7, judgement prediction obtain proposes warning when significantly changing appears in indivedual positions cutting force, and repeating step 3 is to step 7 until all feature cutting force is tending towards normal;

Step 8, according to driving geological information and cutting parameter Information generation processing cutter rail.

The feed angle of each position of described feature calculation when cutting out angle according to tool diameter R with cut wide a _ecalculate feed angle ψ _swith cut out angle ψ _efor:

$\left\{\begin{array}{c}{\mathrm{\&psi;}}_e=\mathrm{\&pi;}/2+\arccos [(R-a_e)/R],a_e<R/2\\ {\mathrm{\&psi;}}_s=\mathrm{\&pi;}\end{array}\right.$

$\left\{\begin{array}{c}{\mathrm{\&psi;}}_e=\arccos [(R-a_e)/R],a_e>R/2\\ {\mathrm{\&psi;}}_s=\mathrm{\&pi;}\end{array}\right.$

Described prediction of Turning Force with Artificial, use mean x to, y to, z to cutting force, formula is as follows, wherein feed rate c=f/ (n*N):

$\stackrel{\&RightArrow;}{F_x}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[K_{\mathrm{t\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}-K_{\mathrm{r\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})]+\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(-K_{\mathrm{t\&sigma;}}\sin \mathrm{\&psi;}+K_{\mathrm{r\&sigma;}}\cos \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_y}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[K_{\mathrm{t\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})+K_{\mathrm{r\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}]-\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(K_{\mathrm{t\&sigma;}}\cos \mathrm{\&psi;}+K_{\mathrm{r\&sigma;}}\sin \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_z}=\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}{(-K_{\mathrm{a\&sigma;}}\cos \mathrm{\&psi;}+K_{\mathrm{a\&sigma;}}\mathrm{\&psi;})}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

The invention has the beneficial effects as follows:

The present invention, by combining with feature, can obtain the cutting force of arbitrary characteristics optional position on aircraft structure; Because prediction of Turning Force with Artificial is just can realize in the automatic process decision process, do not need, by emulation and generation G code, to obtain just can calculating cutting force after cutter rail coordinate, therefore saved the reciprocal process modifications time.Prediction of Turning Force with Artificial based on feature, according to each feature, exclusive technological parameter calculates its cutting force in meeting, therefore can make the cutting parameter of each feature reach maximal value in allowing cutting force, make each feature machining maximizing efficiency, and then the working (machining) efficiency of aircraft structure integral body is maximized.

The present invention by feature, identify and the automatic process decision-making after automatically obtain the cutting force of each feature, do not need to carry out emulation and G code and generate, predict more fast cutting force, shortened the cycle of process optimization, can further improve working (machining) efficiency.

The accompanying drawing explanation

Fig. 1 is the prediction of Turning Force with Artificial method flow diagram based on feature of the present invention;

Fig. 2 is that incision of the present invention cuts out the angle schematic diagram, and its medium speed is that n, feeding are that the f digging angle is ψ _s, cutting out angle is ψ _e;

Fig. 3 is the three-dimensional stress figure that confirmatory experiment of the present invention records jing1-1;

Fig. 4 is the three-dimensional stress figure that confirmatory experiment of the present invention records jing1-2;

Fig. 5 is the three-dimensional stress figure that confirmatory experiment of the present invention records jing1-3;

Embodiment:

Below in conjunction with embodiment and accompanying drawing, the present invention is further illustrated.

As Figure 1-5.

With the cavity feature of aircraft structure as an example, details are as follows by reference to the accompanying drawings for the present embodiment.

Fig. 1 is the prediction of Turning Force with Artificial method flow diagram based on feature of the present invention.As shown in the figure, comprise following steps:

1, part model is inputted to the CAM software systems, part is carried out to pre-service, the input of part feature information can be the characteristic information list of reading in part, or the feature by manually clicking part to be to obtain the driving how much that interior type is relevant, according to drive extract for how much in type cutter orbit making drive wire.

2, carry out process decision, the tool-information obtained comprises that cutter material, cutter sword count N and tool diameter R, and the lathe packets of information is containing the lathe model, and cutting parameter comprises cutting-in a _p, cut wide a _e, the information such as rotation speed n, feeding f.Count N, cut wide a according to the cutter sword _e, rotation speed n can obtain the cutting feed rate:

c=f/(n*N)

In milling, Instantaneous Milling thickness is cyclical variation, and it is the function that becomes the cutter tooth contact angle, with ψ, means instantaneous contact angle, and the expression formula that can obtain cutting swarf thickness is:

t=csinψ

3, digging angle, cut out angle:

As shown in Figure 2, digging angle is ψ _s, cutting out angle is ψ _e, according to tool diameter R with cut wide a _ecalculate for:

$\left\{\begin{array}{c}{\mathrm{\&psi;}}_e=\mathrm{\&pi;}/2+\arccos [(R-a_e)/R],a_e<R/2\\ {\mathrm{\&psi;}}_s=\mathrm{\&pi;}\end{array}\right.$

$\left\{\begin{array}{c}{\mathrm{\&psi;}}_e=\arccos [(R-a_e)/R],a_e>R/2\\ {\mathrm{\&psi;}}_s=\mathrm{\&pi;}\end{array}\right.$

4, the analysis of cutting force

The milling cutter of milling cutting force in carrying out milling process can abbreviation becomes tangentially, radially with axial cutting force, K _{t τ}, K _{r τ}, K _{a τ}for measure shearing force tangentially, radially with axial function coefficient, K _{t σ}, K _{r σ}, K _{a σ}for the cutting edge force coefficient, equation expression is:

F _t(ψ)=K _tτa _pt(ψ)+K _tσa _p

F _r(ψ)=K _rτa _pt(ψ)+K _rσa _p

F _a(ψ)=K _aσa _pt(ψ)+K _aσa _p

By cutting force resolve into x to, y to, z to cutting force:

F _x(ψ)=-F _tcosψ-F _rsinψ

F _y(ψ)=F _tsinψ-F _rcosψ

F _z(ψ)=F _a

Use z _{j, 1}(ψ _j(z)), z _{j, 2}(ψ _j(z)) mean the bound of j tooth cutting tip, the three-dimensional cutting force that can calculate j tooth by integration is:

$F_{x,j}\left({\mathrm{\&psi;}}_j\left(z\right)\right)={\left\{\frac{c}{4}\right[-K_{\mathrm{t\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}+K_{\mathrm{r\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})]+(K_{\mathrm{t\&sigma;}}\sin \mathrm{\&psi;}-K_{\mathrm{r\&sigma;}}\cos \mathrm{\&psi;})\}}_{z_{j,1}\left({\mathrm{\&psi;}}_j\right(z)}^{z_{j,2}\left({\mathrm{\&psi;}}_j\right(z)}$

$F_{y,j}\left({\mathrm{\&psi;}}_j\left(z\right)\right)={\{-\frac{c}{4}[K_{\mathrm{t\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})+K_{\mathrm{r\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}]+(K_{\mathrm{t\&sigma;}}\cos \mathrm{\&psi;}+K_{\mathrm{r\&sigma;}}\sin \mathrm{\&psi;})\}}_{z_{j,1}\left({\mathrm{\&psi;}}_j\right(z)}^{z_{j,2}\left({\mathrm{\&psi;}}_j\right(z)}$

$F_{z,j}\left({\mathrm{\&psi;}}_j\left(z\right)\right)=\frac{1}{2\mathrm{\&pi;}}{(K_{\mathrm{a\&sigma;}}\cos \mathrm{\&psi;}-K_{\mathrm{a\&sigma;}}\mathrm{\&psi;})}_{z_{j,1}\left({\mathrm{\&psi;}}_j\right(z)}^{z_{j,2}\left({\mathrm{\&psi;}}_j\right(z)}$

The instantaneous cutting force that obtains cutter is:

$F_x\left(\mathrm{\&psi;}\right)={\mathrm{\&Sigma;}}_{j=0}^{N-1}{F}_{\mathrm{xj}};F_y\left(\mathrm{\&psi;}\right)={\mathrm{\&Sigma;}}_{j=0}^{N-1}{F}_{\mathrm{yj}};F_z\left(\mathrm{\&psi;}\right)={\mathrm{\&Sigma;}}_{j=0}^{N-1}{F}_{\mathrm{zj}};$

Consider that calculated amount is more consuming time, therefore it is simplified, the expression formula that obtains instantaneous cutting force is:

$\stackrel{\&RightArrow;}{F_x}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[K_{\mathrm{t\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}-K_{\mathrm{r\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})]+\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(-K_{\mathrm{t\&sigma;}}\sin \mathrm{\&psi;}+K_{\mathrm{r\&sigma;}}\cos \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_y}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[K_{\mathrm{t\&tau;}}(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})+K_{\mathrm{r\&tau;}}\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}]-\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(K_{\mathrm{t\&sigma;}}\cos \mathrm{\&psi;}+K_{\mathrm{r\&sigma;}}\sin \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_z}=\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}{(-K_{\mathrm{a\&sigma;}}\cos \mathrm{\&psi;}+K_{\mathrm{a\&sigma;}}\mathrm{\&psi;})}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

5, by trial cut measure (shearing force) cutting force tangentially, radially with axial function coefficient K _{t τ}, K _{r τ}, K _{a τ}with cutting edge force coefficient K _{t σ}, K _{r σ}, K _{a σ}.The detailed process of measuring method is as follows:

1) utilize dynamometer to measure the three-dimensional cutting force of different feed rates under the three-dimensional cutting force of different cutting-ins under identical feed rate and identical cutting-in, data are as shown in table 1;

Table 1

Annotate: table 1 is for of the present invention for measuring the experimental data form of shearing force function coefficient and cutting edge power effect coefficient.Experiment choose respectively under identical cutting-in that different feed rates are tested and identical feed rate under different cutting-ins tested, experiment adopt the Kistler9257B three-dimensional dynamometer record x to, y to, z to the maximum cutting force of three directions as shown in form.

2) every group of cutting force experimental data is brought into to the cutting force analytic expression, by any two groups of data, solves an equation and try to achieve function coefficient, each function coefficient is averaged, finally obtain hot shearing power effect coefficient and cutting edge power effect coefficient under this lathe and be respectively:

Shearing force tangentially, radially, the axial action coefficient is:

K _tτ=3131.1；K _rτ=-1433.3；K _aτ=-455.4；

Cutting edge power tangentially, radially, the axial action coefficient is:

K _tσ=-31.6；K _rσ=17.2；K _aσ=0.3

6, calculate cutting force:

Function coefficient is brought into to the prediction of Turning Force with Artificial formula to be obtained:

$\stackrel{\&RightArrow;}{F_x}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[3131.1\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}+1433.3(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})]+\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(31.6\sin \mathrm{\&psi;}+17.2\cos \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_y}={\left\{\frac{{\mathrm{<figure-callout\; id="8"\; label="Na\; p\; c"\; filenames="HDA0000376150190000031.png"\; state="\{\{state\}\}">Na</figure-callout>}}_{p}c}{8\mathrm{\&pi;}}\right[3131.1(2\mathrm{\&psi;}-\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&psi;})-1433.3\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&psi;}]-\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}(-31.6\cos \mathrm{\&psi;}+17.2\sin \mathrm{\&psi;})\}}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

$\stackrel{\&RightArrow;}{F_z}=\frac{{\mathrm{<figure-callout\; id="2"\; label="Na\; p"\; filenames="HDA0000376150190000022.png"\; state="\{\{state\}\}">Na</figure-callout>}}_p}{2\mathrm{\&pi;}}{(455.4\cos \mathrm{\&psi;}+0.3\mathrm{\&psi;})}_{{\mathrm{\&psi;}}_s}^{{\mathrm{\&psi;}}_e}$

Extraction by automatic feature recognition and cutter rail driving element, obtained the information on all driving limits before emulation, and the technological parameter of processing and cutter, lathe information have been obtained in the process decision process, and then can obtain calculating digging angle, cutting out angle, can calculate the cutting force of optional position.Obvious when higher when the cutting force of finding local feature, have the prompting suggestion to this feature modification cutting parameter.

Whether the prediction of Turning Force with Artificial based on feature, can make the cutting parameter of each feature be tending towards maximal value, also can optimize for the machined parameters of verifying any one feature, by the working (machining) efficiency that improves single feature and then the working (machining) efficiency that improves whole part.

7, to the accuracy experimental verification of prediction of Turning Force with Artificial

A frame class part is carried out to feature identification, obtain machining area and activation bit.Carry out process decision, obtain lathe and tool-information, and choose suitable cutting parameter.The input action coefficient directly carries out prediction of Turning Force with Artificial, for the cutting parameter under type finishing in several cavity features, the cutting force of prediction and the actual cutting force recorded is contrasted.The actual cutting force recorded is as Fig. 3,4,5, and comparing result is as table 2.

Table 2

The part that the present invention does not relate to prior art that maybe can adopt same as the prior art is realized.

Claims (3)

1. the Forecasting Methodology of the cutting force based on feature is characterized in that it comprises the following steps:

Step 1, guiding structure part model, carry out feature identification;

Step 2, according to the feature recognition result, obtain machining area, extract and be used for the driving geological information of Tool-path Generation;

Step 3, the process decision of carrying out obtain tool-information, lathe information, technique information, and definite cutting parameter information; Tool-information comprises that cutter material, cutter sword count N and tool diameter R, and the lathe packets of information is containing the lathe model, and the cutting parameter packets of information is containing cutting-in a _p, cut wide a _e, rotation speed n, feeding f;

The feed angle of step 4, each position of calculated characteristics with cut out angle;

Step 5, by trial cut, measure shearing force tangentially, radially and axial function coefficient K _{t τ}, K _{r τ}, K _{a τ}, measure cutting edge force coefficient K simultaneously _{t σ}, K _{r σ}, K _{a σ};

Step 6, by the shearing force function coefficient of gained and cutting edge force coefficient substitution cutting force formula, calculate cutting force according to technique information;

The cutting force that step 7, judgement prediction obtain proposes warning when significantly changing appears in indivedual positions cutting force, and repeating step 3 is to step 7 until all feature cutting force is tending towards normal;

Step 8, according to driving geological information and cutting parameter Information generation processing cutter rail.

2. Forecasting Methodology as claimed in claim 1, the feed angle that it is characterized in that each position of described feature calculation when cutting out angle according to tool diameter R with cut wide a _ecalculate feed angle ψ _swith cut out angle ψ _efor:

。

3. Forecasting Methodology as described as right 1, is characterized in that, described prediction of Turning Force with Artificial is used

mean x to, y to, z to cutting force, formula is as follows, wherein feed rate c=f/ (n*N):

。

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