Research on cutting quality prediction technology of aviation structural parts based on JAYA-GABP algorithm

Abstract

Aiming at the influence of machining process parameters on the cutting quality of aviation structural parts, this paper studies the cutting quality prediction model based on BP neural network, and uses genetic algorithm and JAYA algorithm to combine and optimize the prediction model. Through analyzing the influencing factors of cutting quality, combined with test data samples, a cutting quality prediction model about cutting force fx, cutting force fy, cutting force fz and cutting temperature is established. A cutting quality prediction system for aviation structural parts was developed, and the effectiveness of the algorithm was verified by experimental data.