Plate laser cutting process parameter optimization method considering sharp corner ablation

Abstract

The invention relates to a plate laser cutting process parameter optimization method considering sharp corner ablation. The method comprises the following steps: carrying out linear cutting and sharp corner cutting orthogonal tests, measuring workpiece quality indexes corresponding to each group of tests, and training a laser cutting quality BP (Back Propagation) neural network model according to obtained test data; and performing process parameter optimization by taking the obtained neural network model as a fitness function of a genetic algorithm to obtain an optimal process parameter. According to the method, the linear cutting quality and the sharp corner cutting quality are taken into consideration, the obtained process parameters are optimized, and the obtained process can have the good kerf width, the good section roughness, the good heat affected zone width and the good slag adhering length, and sharp corner ablation is avoided.

Description

technical field [0001] The invention relates to the field of production and manufacturing, in particular to a process parameter optimization method for plate laser cutting considering sharp corner ablation. Background technique [0002] Compared with traditional cutting, laser cutting has the advantages of no cutting force and high processing efficiency, so it is widely used in sheet metal processing and occupies an important position in sheet metal processing technology. However, there are many process parameters involved in plate laser cutting, including: laser power, auxiliary gas pressure, cutting speed, defocus, duty cycle and pulse frequency. Selecting the optimal set of process parameters from the combination of many process parameters is of great significance to obtain better laser cutting quality of plates. [0003] At present, there are three types of methods for optimizing laser cutting process parameters. One is to use traditional physical modeling methods to es...

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Problems solved by technology

[0003] At present, there are three types of methods for optimizing laser cutting process parameters. One is to use traditional physical modeling methods to establish a model between process parameters and cutting quality, and then optimize process parameters. The accuracy of this type of method depends largely on In the actual laser cutting process, these parameters are often coupled and time-varying, so the judgment method based on physical modeling is not accurate

The second is an experiment-based method, which takes laser cutting process parameters as experimental factors, conducts a large number of laser cutting experiments, obtains the variation of laser cutting quality with each process parameter according to the test data, and gives suggestions for process parameter optimization, but There is a complex coupling relationship between various process parameters and cutting quality. For example, increasing the laser power will reduce the roughness of the cut surface, but it will also make the quality of the kerf worse. It is difficult to give a reasonable answer for such a complex coupling relationship based on the experimental method. Suggestions for optimization of process parameters

[0006] Most methods use the weighted summation of the laser cutting quality evaluation indicators (kerf width, cut surface roughness, heat-affected zone width, and slag length) to be unified into one evaluation index and then optimize the process parameters, but this method cannot be used for each index. Make a reasonable evaluation of the extreme value distribution

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