Multi-target optimization method for numerical control processing parameters

A multi-objective optimization and processing parameter technology, applied in the direction of program control, computer control, general control system, etc., can solve problems affecting the optimization effect, achieve the effect of improving the optimization effect and overcoming the disadvantages of subjectivity

Inactive Publication Date: 2017-05-31
TIANJIN UNIV OF COMMERCE
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Problems solved by technology

The first two methods are human-made decisions at the beginning of optimization, and the third method is to search for optimization first and then make decisions, but th

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  • Multi-target optimization method for numerical control processing parameters
  • Multi-target optimization method for numerical control processing parameters
  • Multi-target optimization method for numerical control processing parameters

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Embodiment Construction

[0015] Below, the substantive features and advantages of the present invention will be further described in conjunction with examples, but the present invention is not limited to the listed examples.

[0016] Next, the implementation process of the present invention will be described in detail by taking helical milling as an example. In the process of spiral milling CNC machining, the tool 1 performs spiral motion on the surface of the workpiece 2 to mill on the working surface, see figure 2 shown.

[0017] see figure 1 As shown, a multi-objective optimization method for NC machining parameters includes the following steps:

[0018] S101, according to the numerical control machining process, analyze the machining requirements, and establish a multi-objective optimization mathematical model reflecting the relationship between the determined design variables and the multi-objectives to be optimized;

[0019] 1). Determine the design variables that affect the multi-objective ...

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Abstract

The invention relates to a multi-target optimization method for numerical control processing parameters. The method comprises the steps of analyzing a processing request according to a numerical control processing process, and establishing a multi-target optimization mathematical model which represents a relationship between a definite designing variable and a to-be-optimized multi-target variable; solving the multi-target optimization mathematical model by means of a Pareto genetic algorithm, and obtaining a Pareto optimal solution set between the designing variable and the multi-target variable; analyzing relationships between multi-target variable parameters in the Pareto optimal solution set, establishing a contradiction matrix table between target variables according to a TRIZ theory, then analyzing a problem according to a TRIZ theory invention principle, and determining a set of optimal processing parameters from the Pareto optimal solution set according to the analysis result. The multi-target optimization method has advantages of performing an optimization-and-decision mode in multi-target optimization of numerical control processing parameters, overcoming a subjective defect in decision based on preference or experience, truly realizing and perfecting the optimization-and-decision solving mode, and improving optimization effect.

Description

technical field [0001] The invention belongs to the technical field of numerical control machining parameter optimization, and in particular relates to a multi-objective optimization method of numerical control machining parameters. Background technique [0002] The selection of NC processing parameters is related to the productivity, production cost and processing quality of the processing system. At present, most of the optimization methods are used to establish the optimization model of the processing system parameters, and the optimal processing parameters are obtained through a certain optimization algorithm to achieve the purpose of optimizing the processing process. From the perspective of the development of optimization algorithms, it is developing in the direction of intelligence, such as: genetic algorithm, ant colony algorithm and particle swarm algorithm and other intelligent algorithms. For the optimization model, there are many optimization objectives based on...

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Application Information

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IPC IPC(8): G05B19/408
CPCG05B19/4083G05B2219/35356
Inventor 刘恒丽
Owner TIANJIN UNIV OF COMMERCE
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