CN105446269B - Contour curve numerical control code generating method based on genetic algorithm and its numerically-controlled machine tool - Google Patents
Contour curve numerical control code generating method based on genetic algorithm and its numerically-controlled machine tool Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/408—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
Contour curve numerical control code generating method based on genetic algorithm and its numerically-controlled machine tool are used for numerically-controlled machine tool, including following procedure of processing：(1) to the contour curve founding mathematical models of workpieces processing in digital control system；(2) genetic algorithm is programmed to iterative calculation in computer, seeks approaching node；(3) generate and export the processing curve Path numerical control code of process tool；(4) workpieces processing is put into machine table, is positioned and is fixed by fixture；(5) knife is gone out to knife, positioning machining starting point position by tool magazine；(6) process tool according to acquisition processing curve Path numerical control code, in machine table to workpieces processing process.The present invention proposes the contour curve numerical control code generating method based on genetic algorithm and is applied to numerically-controlled machine tool, directly effectively determine optimal processing curve Path, process tool is set to be accurately finished digital control processing, improve the working efficiency and quality of numerically-controlled machine tool, it is easy to operate direct, high precision machining.
Description
Technical field
The present invention relates to technical fields of mechanical processing, more particularly to the contour curve numerical control code based on genetic algorithm generates
Method and its numerically-controlled machine tool.
Background technology
Numerically-controlled machine tool is a kind of automated machine tool equipped with program control system, with the quick hair of mechanotronics
Exhibition, numerically-controlled machine tool equipment have been obtained for being widely applied in field of machining, and after decades of development, technical merit is big
Amplitude improves, and the function of numerically-controlled machine tool product is gradually improved, and specification is increasingly complete, but only the variation in function and specification with
It is abundant to meet processing needs.
At present using numerically-controlled machine tool in the digital control processing of the appearance profile curve of workpieces processing, generally using straight line or
Circular arc goes to approach its node, and the feed processing approached.Include to the main method of free curve beeline approaching node etc.
Spacing, etc. chord lengths and equal error approximationd node, wherein the method for grade error beeline approach node can make it is all approach line segments mistake
Difference is equal, can ensure the mismachining tolerance for approaching node, but in actual computer application, free curve equal error straight line is forced
The geometric algorithm programming of nearly node is complicated, is difficult to be directly realized by, and complex curve is difficult to effectively determine optimal processing bent
Face track, can only by numerical analysis in processing method it is equivalent replace realize, numerically-controlled machine tool process tool to workpiece
The manufacturing procedure of appearance profile curve is cumbersome, processing curve track precision is low and complicated for operation, therefore there is no well
Geometric algorithm using free curve grade error beeline approach node applies in the processing of numerically-controlled machine tool machinery.
Invention content
It is an object of the invention to propose high precision machining, the contour curve numerical control generation easy to operate based on genetic algorithm
Code generating method.
It is another object of the present invention to propose a kind of numerically-controlled machine tool suitable for workpieces processing appearance profile curve.
For this purpose, the present invention uses following technical scheme：
Contour curve numerical control code generating method based on genetic algorithm is used for numerically-controlled machine tool, including following procedure of processing：
(1) to the contour curve founding mathematical models of workpieces processing in digital control system；
(2) genetic algorithm is programmed to iterative calculation in computer, seeks effectively approaching node；
(3) generate and export the processing curve Path numerical control code of process tool；
(4) workpieces processing is put into machine table, is positioned and is fixed by fixture；
(5) knife is gone out to knife, positioning machining starting point position by tool magazine；
(6) the processing curve Path numerical control code that the process tool is obtained according to step (3), in the machine table
The workpieces processing is processed, finished product is obtained.
It further illustrates, the founding mathematical models include the following steps：
(1) allowable error, fluctuating error and the slope for approaching straight line are determined；
(2) it determines free curve equation and approaches linear equation；
(3) object function, constraints and end condition are determined.
It further illustrates, the genetic algorithm iterative calculation includes the following steps：
(1) free curve parameter and machining starting point coordinate are given；
(2) real coding is used, setting initial population individual is random to generate individual position coordinates, calculates all individuals
Object function；
(3) use the method choice of roulette preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated
It sets；The method to be made a variation using real number carries out mutation operation to next-generation individual；
(4) target function value of all individuals is calculated, weighted average finds out the average criterion functional value of the population；
(5) magnitude relationship of the average criterion functional value and fluctuating error is evaluated, i.e. population is whole in fluctuating error model
It is the optimal solution of object function in enclosing, the average value for storing current population at individual position coordinates is next node coordinate；Otherwise it returns
Return step (3) iteration.
A kind of numerically-controlled machine tool suitable for workpieces processing appearance profile curve, including machine table, process tool and numerical control system
System, the digital control system are provided with the genetic algorithm subsystem for determining processing curve Path, genetic algorithm
System determines that the movement of the tool sharpening, the process tool are controlled by the digital control system according to the initial position of machined surface
Its processing to the appearance profile curve of workpiece.
The genetic algorithm subsystem is changing in computer programming by founding mathematical models and use genetic algorithm
In generation, calculates solving-optimizing, and obtain the processing curve track of the process tool approaches node.
It further illustrates, the appearance profile curve of the workpieces processing is free curve.
It further illustrates, the operating procedure of the genetic algorithm subsystem is as follows：
A founding mathematical models
(1) allowable error, fluctuating error and the slope for approaching straight line are determined；
(2) it determines free curve equation and approaches linear equation；
(3) object function, constraints and end condition are determined；
B genetic algorithms iterate to calculate solving-optimizing
(1) free curve parameter and machining starting point coordinate are given；
(2) real coding is used, setting initial population individual is random to generate individual position coordinates, calculates all individuals
Object function；
(3) use the method choice of roulette preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated
It sets；The method to be made a variation using real number carries out mutation operation to next-generation individual；
(4) target function value of all individuals is calculated, weighted average finds out the average criterion functional value of the population；
(5) magnitude relationship of the average criterion functional value and fluctuating error is evaluated, i.e. population is whole in fluctuating error model
It is the optimal solution of object function in enclosing, the average value for storing current population at individual position coordinates is next node coordinate；Otherwise it returns
Return step (3) iteration.
It further illustrates, the object function is the free curve and approaches the error of straight line.
It further illustrates, the constraints is to approach node on free curve.
It further illustrates, the stopping criterion for iteration is allowable range of error.
Beneficial effects of the present invention：The genetic algorithm subsystem is arranged in the present invention, by the computer programming of genetic algorithm
Apply in the numerical control code generation of numerically-controlled machine tool, directly effectively determine optimal processing curve Path, makes described add
Work cutter effectively and accurately carries out digital control processing to workpiece configurations contour curve, improves the working efficiency and matter of the numerically-controlled machine tool
Amount, easy to operate direct, high precision machining.
Description of the drawings
Fig. 1 is the system framework figure of the numerically-controlled machine tool of one embodiment of the invention；
Fig. 2 is the genetic algorithm flow chart of one embodiment of the invention；
Fig. 3 is the genetic algorithm flow chart in the genetic algorithm subsystem of one embodiment of the invention.
Specific implementation mode
Technical solution to further illustrate the present invention below with reference to the accompanying drawings and specific embodiments.
Contour curve numerical control code generating method based on genetic algorithm is used for numerically-controlled machine tool, including following procedure of processing：
(1) to the contour curve founding mathematical models of workpieces processing in digital control system；
(2) genetic algorithm is programmed to iterative calculation in computer, seeks effectively approaching node；
(3) generate and export the processing curve Path numerical control code of process tool；
(4) workpieces processing is put into machine table, is positioned and is fixed by fixture；
(5) knife is gone out to knife, positioning machining starting point position by tool magazine；
(6) the processing curve Path numerical control code that the process tool is obtained according to step (3), in the machine table
The workpieces processing is processed, finished product is obtained.
Genetic algorithm is applied in the numerical control code generation of numerically-controlled machine tool, processing curve Path is determined, for controlling
Processing of the process tool processed to workpiece, makes the process tool be accurately finished the processing of workpiece configurations contour curve, improves
It is easy to operate to improve the processing efficiency and quality of numerically-controlled machine tool simultaneously to the machining accuracy of workpiece configurations contour curve
Directly, high precision machining.
It further illustrates, the founding mathematical models include the following steps：
(1) allowable error, fluctuating error and the slope for approaching straight line are determined；
(2) it determines free curve equation and approaches linear equation；
(3) object function, constraints and end condition are determined.
The problem of grade error beeline approach node coordinate, is changed into the function optimization of belt restraining by founding mathematical models
Problem, the accuracy of the raising acquisition processing curve Path numerical control code, the needs being satisfied in the programming of computer,
To effectively obtain the processing curve track of the cutter, ensure the accuracy and stability of tool sharpening.
It further illustrates, the genetic algorithm iterative calculation includes the following steps：
(1) free curve parameter and machining starting point coordinate are given；
(2) real coding is used, setting initial population individual is random to generate individual position coordinates, calculates all individuals
Object function；
(3) use the method choice of roulette preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated
It sets；The method to be made a variation using real number carries out mutation operation to next-generation individual；
(4) target function value of all individuals is calculated, weighted average finds out the average criterion functional value of the population；
(5) magnitude relationship of the average criterion functional value and fluctuating error is evaluated, i.e. population is whole in fluctuating error model
It is the optimal solution of object function in enclosing, the average value for storing current population at individual position coordinates is next node coordinate；Otherwise it returns
Return step (3) iteration.
It is iterated to calculate in computer programming by using genetic algorithm, what can effectively be sought accurately approaches node,
To reduce difficulty of the numerically-controlled machine tool to workpieces processing appearance profile curve, the machining accuracy of numerically-controlled machine tool is improved.
A kind of numerically-controlled machine tool suitable for workpieces processing appearance profile curve, as shown in Figure 1, including machine table, processing knife
Tool and digital control system, it is characterised in that：The digital control system is provided with the genetic algorithm for determining processing curve Path
Subsystem, the genetic algorithm subsystem determine the movement of the tool sharpening, the processing according to the initial position of machined surface
Cutter controls its processing to the appearance profile curve of workpiece by the digital control system.
The genetic algorithm subsystem is changing in computer programming by founding mathematical models and use genetic algorithm
In generation, calculates solving-optimizing, and obtain the processing curve track of the process tool approaches node.
The numerically-controlled machine tool of the present invention is that the genetic algorithm subsystem is arranged by the digital control system to determine to add
Work curved surface Path, to control processing of the process tool to workpiece configurations contour curve, original for shape
The geometry computational methods of contour curve are difficult to use in a computer, and the process tool can not be effectively according to optimal
Processing curve track is processed, and can only be replaced realizing come equivalent with processing by numerical analysis, therefore institute is arranged in the present invention
Genetic algorithm subsystem is stated, is iterated to calculate by founding mathematical models and using genetic algorithm, to obtain processing curve track
Approach node, directly effectively determine optimal processing curve Path, then the process tool can accurately pair plus
Work workpiece configurations contour curve is processed, and improves the working efficiency and processing quality of the numerically-controlled machine tool, process operation is simple,
High precision machining.It is to be appreciated that the subsystem can be software or firmware, wherein software is equipped with function or subprogram.
It further illustrates, the appearance profile curve of the workpieces processing is free curve.
Free curve is the workpiece configurations contour curve being commonly encountered in digital control processing, and the genetic algorithm subsystem is by building
It founds mathematical model and the digital control processing to free curve is iterated to calculate using genetic algorithm, realize that free curve equal error straight line is forced
The geometry computational methods of nearly node program in computer and apply to numerically-controlled machine tool, reduce the difficulty of processing of numerically-controlled machine tool,
Improve machining accuracy.
It further illustrates, as shown in figure 3, the operating procedure of the genetic algorithm subsystem is as follows：
A founding mathematical models
(1) allowable error, fluctuating error and the slope for approaching straight line are determined；
(2) it determines free curve equation and approaches linear equation；
(3) object function, constraints and end condition are determined；
B genetic algorithms iterate to calculate solving-optimizing
(1) free curve parameter and machining starting point coordinate (X are given0,Y0)；
(2) use real coding, setting initial population individual random to generate individual position coordinates (Xi,Yi) (i=1 ...,
N, n are population at individual number), calculate the object function of all individuals；
(3) use the method choice of roulette preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated
It sets；The method to be made a variation using real number carries out mutation operation to next-generation individual；
(4) the target function value F (x of all individuals are calculatedi), weighted average finds out the average criterion functional value of the population：
(5) magnitude relationship of the average criterion functional value F (x) and fluctuating error is evaluated, i.e., population is whole misses in fluctuation
It is the optimal solution of object function in poor range, the average value for storing current population at individual position coordinates is next node coordinate；It is no
Then return to step (3) iteration.
Specific mathematical model, which establishes thinking, is：The problem of grade error beeline approach node coordinate, is changed into belt restraining
Function optimization problem, and solution is optimized to realize the solution of grade error beeline approach node coordinate using genetic algorithm.Number
It learns and indicates as follows：
If free curve equation is：Y=f (x)
Allowable error is：e
Fluctuating error is：bn
The starting point coordinate for approaching straightway is：(X0,Y0)
The terminal point coordinate for approaching straightway is：(X,Y)
The coordinate of point on free curve is：(xj, yj)
The slope for approaching straight line is：K=(Y-Y0)/(X-X0)
The equation for approaching straight line is：y-Y0=k (x-X0), i.e. kx-y-kX0+Y0=0
Approach straight line is with the error distance put on free curve：
The error distance for approaching straight line and free curve is：D=max { dj}
Mathematical model is as follows：
Object function is：F (x)=| d-e |
Constraints is：Y=f (x)
End condition is：F(x)≤bn
As shown in Fig. 2, genetic algorithm, which from the simulation to biological evolution process, that is, simulates biotic population, adapts to existence ring
The natural selection process in border, the genetic algorithm are passed through to the initialization of population at individual, selection, evolution, variation, evaluation and procreation
Process obtain the best population at individual of Environmental Suitability.Genetic algorithm is initialized as the random population at individual of a group, often
An individual obtains the gene of itself by coding, and the environment that each individual can be obtained by calculating target function value adapts to
Degree.In the seed procedure of individual per a generation, the population at individual and superseded fitness that natural environment can select fitness high are low
Individual.Selected cognition carries out gene intersection procreation and obtains follow-on population at individual, and next-generation during procreation
A generation known from experience along with genetic mutation.The new population at individual obtained can recalculate the environment fitness of each individual,
And enter the seed procedure of next-generation individual.Finally, by the continuous procreation of population at individual, population at individual gene can tend to be best
Environment fitness, i.e. population integrally levels off to the optimal solution of object function.
As shown in figure 3, the present invention applies to the genetic algorithm in the numerically-controlled machine tool, i.e., in grade error beeline approach
Individual node is solved using genetic algorithm in node, on the basis of founding mathematical models, by being initialized, being selected, again
Group, variation and the process of evaluation, a body position are equivalent to the node coordinate, evaluate the average criterion functional value and wave
The magnitude relationship of dynamic error, is constantly iterated selection, evolution, variation and evaluation, and the individual of population is made to level off to best position
Coordinate is set, i.e., the best approximation node coordinate of the described free curve improves to obtain optimal processing curve track to described
The machining accuracy of workpiece configurations contour curve.
It further illustrates, the object function is the free curve and approaches the error of straight line.
Object function is set as the free curve and approaches the error of straight line, to evaluate average criterion functional value and wave
The magnitude relationship of dynamic error, judges whether the error for approaching node described in guarantee in the range of fluctuating error in a certain range
It is interior.
It further illustrates, the constraints is to approach node on free curve.
Constraints is set as approaching node on free curve, overcoming original can not judge straight line and free curve
The shortcomings that whether intersecting be changed into the function optimization problem of belt restraining the problem of grade error beeline approach node coordinate, ensured
The striked precision for approaching node.
It further illustrates, the stopping criterion for iteration is allowable range of error.
Using allowable range of error as the condition of iteration ends, ensure striked to approach what node coordinate allowed in error
In range, that is, ensure the mismachining tolerance for approaching node, to ensure processing of the process tool to workpiece configurations contour curve
Precision.
The technical principle of the present invention is described above in association with specific embodiment.These descriptions are intended merely to explain the present invention's
Principle, and it cannot be construed to limiting the scope of the invention in any way.Based on the explanation herein, the technology of this field
Personnel would not require any inventive effort the other specific implementation modes that can associate the present invention, these modes are fallen within
Within protection scope of the present invention.
Claims (2)
1. the contour curve numerical control code generating method based on genetic algorithm, it is characterised in that：For numerically-controlled machine tool, including it is as follows
Procedure of processing：
(1) to the contour curve founding mathematical models of workpieces processing in digital control system；
(2) genetic algorithm is programmed to iterative calculation in computer, seeks effectively approaching node；
(3) generate and export the processing curve Path numerical control code of process tool；
(4) workpieces processing is put into machine table, is positioned and is fixed by fixture；
(5) knife is gone out to knife, positioning machining starting point position by tool magazine；
(6) the processing curve Path numerical control code that the process tool is obtained according to step (3), in the machine table to institute
Workpieces processing processing is stated, finished product is obtained；
The founding mathematical models include the following steps：
I, determines allowable error, fluctuating error and the slope for approaching straight line；
II, determines free curve equation and approaches linear equation；
III, determines object function, constraints and end condition；
The genetic algorithm iterative calculation includes the following steps：
1. given free curve parameter and machining starting point coordinate；
2. using real coding, setting initial population individual is random to generate individual position coordinates, calculates the target letter of all individuals
Number；
3. the method choice using roulette is preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated；Profit
The method to be made a variation with real number carries out mutation operation to next-generation individual；
4. calculating the target function value of all individuals, weighted average finds out the average criterion functional value of the population；
5. evaluating the magnitude relationship of the average criterion functional value and fluctuating error, i.e., population is whole is within the scope of fluctuating error
The optimal solution of object function, the average value for storing current population at individual position coordinates are next node coordinate；Otherwise return to step
3. iteration；
The object function is the free curve and approaches the error of straight line, and the constraints is to approach node in free song
On line, the stopping criterion for iteration is allowable range of error.
2. a kind of numerically-controlled machine tool suitable for workpieces processing appearance profile curve, including machine table, process tool and digital control system,
It is characterized in that：The digital control system is provided with the genetic algorithm subsystem for determining processing curve Path, the something lost
Propagation algorithm subsystem determines the movement of the tool sharpening according to the initial position of machined surface, and the process tool is by the numerical control
System controls its processing to the appearance profile curve of workpiece；
The genetic algorithm subsystem is the iteration meter by founding mathematical models and using genetic algorithm in computer programming
Solving-optimizing is calculated, obtain the processing curve track of the process tool approaches node；
The appearance profile curve of the workpieces processing is free curve；
The operating procedure of the genetic algorithm subsystem is as follows：
A founding mathematical models
I, determines allowable error, fluctuating error and the slope for approaching straight line；
II, determines free curve equation and approaches linear equation；
III, determines object function, constraints and end condition；
B genetic algorithms iterate to calculate solving-optimizing
1. given free curve parameter and machining starting point coordinate；
2. using real coding, setting initial population individual is random to generate individual position coordinates, calculates the target letter of all individuals
Number；
3. the method choice using roulette is preferably individual；Using intermediate recombination form, the position of next-generation individual is calculated；Profit
The method to be made a variation with real number carries out mutation operation to next-generation individual；
4. calculating the target function value of all individuals, weighted average finds out the average criterion functional value of the population；
5. evaluating the magnitude relationship of the average criterion functional value and fluctuating error, i.e., population is whole is within the scope of fluctuating error
The optimal solution of object function, the average value for storing current population at individual position coordinates are next node coordinate；Otherwise return to step
3. iteration；
The object function is the free curve and approaches the error of straight line；
The constraints is to approach node on free curve；
The stopping criterion for iteration is allowable range of error.
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| CN108333937B (en) * | 2018-02-02 | 2021-03-23 | 江苏师范大学 | Contour machining method for multi-axis linkage machine tool |
| CN108994553A (en) * | 2018-07-06 | 2018-12-14 | 宁波联合蓝光科技有限公司 | A kind of spur gear numerical-control processing method |
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| CN110866309B (en) * | 2019-11-15 | 2023-05-23 | 中车南京浦镇车辆有限公司 | Intelligent calculation method for maximum outline of metro vehicle based on metro limit |
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