Neural network laser cutting quality prediction method

Abstract

The invention discloses a neural network laser cutting quality prediction method. The method comprises the following steps: taking a to-be-processed original part as a sample to carry out a cutting experiment according to different laser cutting parameter sets; acquiring experimental data of the cutting experiment; constructing a neural network, and setting a transmission function, a learning rate, a training frequency, a training target, a momentum factor and a training parameter of the neural network; preprocessing the experimental data, and training and verifying the neural network by usingthe experimental data; and simulating a cutting process by utilizing the neural network model to search an optimal target laser cutting parameter set meeting the quality requirement. According to themethod, experimental data is acquired by using fewer cutting experiments to perform training modeling on the three-layer reverse transmission neural network, all laser cutting parameters are predicted by using the three-layer reverse transmission neural network, and a target prediction result meeting customer quality requirements is selected; the method has the advantages of being short in period, low in cost, high in efficiency, capable of obtaining the optimal laser cutting parameters more quickly and the like.

Description

technical field [0001] The invention relates to the technical field of laser cutting, in particular to a neural network laser cutting quality prediction method. Background technique [0002] Laser cutting is the use of high-power-density laser beams to irradiate the material to be cut, so that the material is quickly heated to the vaporization temperature, evaporates to form holes, and completes the cutting of the material with the relative movement between the beam and the material. [0003] In the process of industrial laser cutting, the cutting process of some materials has high requirements on the quality of laser cutting. If a cutting equipment is to be able to process materials with specific cutting quality requirements, it is necessary for the craftsmen to obtain the laser cutting experiments to achieve the requirements. The laser cutting parameters required by the quality, adjust the machine according to the laser cutting parameters and verify the actual effect, and ...

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Problems solved by technology

[0004] The present invention provides a neural network laser cutting quality prediction method, which aims to solve the problem of high cost, long cycle and waste of efficiency in the actual production of the method of obtaining laser cutting parameters according to experiments to meet the processing business with certain cutting requirements in the prior art question

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