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Physics-Guided Deep Learning Method for Tool Condition Monitoring in Smart Machining System 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2023
作者:  Li, Shenshen;  Lin, Xin;  Shi, Hu;  Shi, Yungao;  Zhu, Kunpeng
收藏  |  浏览/下载：13/0  |  提交时间：2023/11/17
Deep learning  physics-guided data model  tool condition monitoring  
Online tool wear monitoring by super-resolution based machine vision 期刊论文
COMPUTERS IN INDUSTRY, 2023, 卷号: 144
作者:  Zhu, Kunpeng;  Guo, Hao;  Li, Si;  Lin, Xin
收藏  |  浏览/下载：41/0  |  提交时间：2022/12/22
Single image super -resolution  Sparse decomposition  Micro machining  Tool monitoring  
Generic Cutting Force Modeling with Comprehensively Considering Tool Edge Radius, Tool Flank Wear and Tool Runout in Micro-End Milling 期刊论文
MICROMACHINES, 2022, 卷号: 13
作者:  Gao, Shuaishuai;  Duan, Xianyin;  Zhu, Kunpeng;  Zhang, Yu
收藏  |  浏览/下载：33/0  |  提交时间：2022/12/23
cutting force  mechanical modeling  micro-end milling  tool edge radius  tool flank wear  tool runout  
Interpretable deep learning approach for tool wear monitoring in high-speed milling 期刊论文
COMPUTERS IN INDUSTRY, 2022, 卷号: 138
作者:  Guo, Hao;  Zhang, Yu;  Zhu, Kunpeng
收藏  |  浏览/下载：47/0  |  提交时间：2022/05/16
Tool wear monitoring  Interpretability  Deep learning  Attention  
Pyramid LSTM Network for Tool Condition Monitoring 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 卷号: 71
作者:  Guo, Hao;  Lin, Xin;  Zhu, Kunpeng
收藏  |  浏览/下载：29/0  |  提交时间：2022/12/23
Feature extraction  Monitoring  Milling  Computational modeling  Hidden Markov models  Employee welfare  Task analysis  Auto-encoder  network structure  pyramid long short-term memory (LSTM)  tool wear monitoring  visual analysis  
In-situ tool wear area evaluation in micro milling with considering the influence of cutting force 期刊论文
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 卷号: 161
作者:  Li, Si;  Zhu, Kunpeng
收藏  |  浏览/下载：57/0  |  提交时间：2021/08/30
Micro milling  Tool wear area  Empirical statistical model  Milling force  Grey relational degree  
Tool wear estimation and life prognostics in milling: Model extension and generalization 期刊论文
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 卷号: 155
作者:  Zhang, Yu;  Zhu, Kunpeng;  Duan, Xianyin;  Li, Si
收藏  |  浏览/下载：58/0  |  提交时间：2021/04/26
Milling  Tool wear modeling and monitoring  Adjustable coefficients  Generalization  Genetic algorithm  
An Improved Tool Wear Monitoring Method Using Local Image and Fractal Dimension of Workpiece 期刊论文
MATHEMATICAL PROBLEMS IN ENGINEERING, 2021, 卷号: 2021
作者:  Yu, Haicheng;  Wang, Kun;  Zhang, Ruhai;  Wu, Xiaojun;  Tong, Yulin;  Wang, Ruiyuan;  He, Dedao
收藏  |  浏览/下载：50/0  |  提交时间：2021/08/30
A Switching Hidden Semi-Markov Model for Degradation Process and Its Application to Time-Varying Tool Wear Monitoring 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 卷号: 17
作者:  Liu, Tongshun;  Zhu, Kunpeng
收藏  |  浏览/下载：52/0  |  提交时间：2021/03/15
Condition monitoring  degradation process  remaining useful life (RUL)  switching hidden semi-Markov model (SHSMM)  tool wear monitoring (TWM)  
Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method 期刊论文
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020
作者:  Liu, Tongshun;  Zhu, Kunpeng;  Wang, Gang
收藏  |  浏览/下载：66/0  |  提交时间：2020/12/28
Micro-milling  Cutting force model  Tool runout  Cutting force coefficient identification  Tool wear monitoring