重庆科技学院学报（自然科学版）2024，Vol.26Issue(3)：36-41,6.DOI:10.19406/j.issn.1673-1980.2024.03.006
基于神经网络的液压机状态监测系统研究
Research on Hydraulic Press Status Monitoring System Based on Neural Networks
摘要
Abstract
Neural network is an artificial intelligence model similar to the human nervous system,which can com-bine and filter traditional monitoring data to improve the accuracy of fault detection.To improve the fault evaluation performance of the hydraulic press status monitoring system,a new solution for equipment status monitoring is pro-posed by utilizing the advantages of neural network-based machine learning methods.Neural network model was trained and features were extracted from a large amount of data to achieve accurate identification of faults in hydrau-lic press monitoring systems.关键词
神经网络/液压机/状态监测/机器学习Key words
neural networks/hydraulic presses/state monitoring/machine learning分类
机械制造引用本文复制引用
王建军,郝素兰..基于神经网络的液压机状态监测系统研究[J].重庆科技学院学报（自然科学版）,2024,26(3):36-41,6.基金项目
安徽省高校自然科学研究重点项目"基于云平台的液压机液压系统故障智能诊断技术研究"(KJ2020A1108) （KJ2020A1108）
安徽省2021年高校学科(专业)拔尖人才学术资助项目"大型运载装备多机分布式协同控制智能化和关键技术研究"(GXB-JZD2021100) （专业）
安徽机电职业技术学院2019年特色高水平专业建设项目"机械设计与制造专业"(2019TGZY01) （2019TGZY01）
