测控技术2024，Vol.43Issue(7)：65-70,6.DOI:10.19708/j.ckjs.2024.07.009
基于GA-BP算法激光设备故障预测技术研究
Research on Fault Prediction Technology of Laser Equipment Based on GA-BP Algorithm
摘要
Abstract
Aiming at the frequent unplanned shutdown of laser equipment,a method based on genetic algorithm(GA)is proposed to optimize the BP neural network and estalbish the fault prediction model of laser equip-ment.The historical data of the laser equipment is used to train and adjust the prediction algorithm,analyze the real-time data collected by the laser equipment,predict the probability of fault according to the algorithm mod-el,maintain the laser equipment in advance,reduce the number of unplanned shutdown,and improve the effec-tive running time of the laser equipment.By measuring the data changes of the laser equipment when cutting parts under various conditions,the GA is used to optimize the BP neural network algorithm to establish a fault prediction model of laser equipment.The data of cutting parts in various situations are selected for simulation prediction and verification.The gas pressure,laser power,cutting speed,as well as the calculated following er-ror,acceleration,and temperature of each axis in various situations during the cutting process are used as the input of the model.The roughness is used as the output of the model.The results show that the prediction effect and prediction accuracy of the model optimized by GA are better than that of the model without optimization by GA,and after GA optimization the prediction accuracy and convergence speed of the model's roughness are im-proved.关键词
激光设备/遗传算法/故障预测/粗糙度Key words
laser equipment/GA/fault prediction/roughness分类
机械工程引用本文复制引用
路世强,于嘉龙,陈月娥..基于GA-BP算法激光设备故障预测技术研究[J].测控技术,2024,43(7):65-70,6.基金项目
山东省重点研发计划(2021S020201-03004) （2021S020201-03004）
