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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:2/0
  |  
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:16/0
  |  
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:15/0
  |  
提交时间:2022/12/23
cutting force
mechanical modeling
micro-end milling
tool edge radius
tool flank wear
tool runout
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:6/0
  |  
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:40/0
  |  
提交时间:2021/08/30
Micro milling
Tool wear area
Empirical statistical model
Milling force
Grey relational degree
Optimization of milling process parameters and prediction of abrasive wear rate increment based on cutting force experiment
期刊论文
ADVANCES IN MECHANICAL ENGINEERING, 2021, 卷号: 13, 期号: 8
作者:
Li, Fei
;
Liu, Jun
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  |  
浏览/下载:7/0
  |  
提交时间:2021/10/14
Abrasive wear rate increment
gray relational method
parameter optimization
BP neural network
increment prediction
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:103/0
  |  
提交时间:2020/12/28
Micro-milling
Cutting force model
Tool runout
Cutting force coefficient identification
Tool wear monitoring
Mechanistic prediction for cutting force in rotary ultrasonic machining of BK7 glass based on probability statistics
期刊论文
ULTRASONICS, 2020, 卷号: 101
作者:
Lv, Dongxi
;
Yan, Chun
;
Chen, Gang
;
Liu, Dong
;
Wu, Xiaofei
收藏
  |  
浏览/下载:43/0
  |  
提交时间:2020/12/16
ELECTROPLATED DIAMOND WHEELS
HIGH-FREQUENCY VIBRATION
SURFACE-ROUGHNESS
SILICON-NITRIDE
DAMAGE
WEAR
A generic tool wear model and its application to force modeling and wear monitoring in high speed milling
期刊论文
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 卷号: 115, 期号: 无, 页码: 147-161
作者:
Zhu, Kunpeng
;
Zhang, Yu
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  |  
浏览/下载:66/0
  |  
提交时间:2019/12/25
Tool wear monitoring
Adjustable coefficients
Tool life
High speed milling
Milling force
Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction
期刊论文
COMPUTERS IN INDUSTRY, 2019, 卷号: 111, 页码: 1-14
-
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2020/01/03
Smart manufacturing
Deep learning
Bi-Directional GRU
Tool wear prediction
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