北京航空航天大学主页平台系统 wangyiwei--Home-- Event-driven tool condition monitoring methodology considering tool life prediction based on industrial internet

Personal Information

MORE+

Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

E-Mail:

Date of Employment:2018-11-01

School/Department:机械工程及自动化学院

Education Level:博士研究生

Business Address:北京市海淀区学院路37号新主楼A座506

Gender:Female

Contact Information:http://www.me.buaa.edu.cn/info/1071/4891.htm

Degree:Doctoral Degree in Engineering

Status:Employed

Alma Mater:法国图卢兹国立应用科学学院

王艺玮

Gender:Female

Education Level:博士研究生

Alma Mater:法国图卢兹国立应用科学学院

Paper

Current position: Home / Paper

Event-driven tool condition monitoring methodology considering tool life prediction based on industrial internet

Impact Factor:12.1
DOI number:10.1016/j.jmsy.2020.11.019
Journal:Journal of Manufacturing Systems
Co-author:Lianyu Zheng
First Author:Yahui Wang
Indexed by:Journal paper
Correspondence Author:Yiwei Wang
First-Level Discipline:Mechanical Engineering
Document Type:J
Volume:58
Page Number:205-222
Translation or Not:no
Date of Publication:2021-07-30
Included Journals:SCI
Links to published journals:https://www.sciencedirect.com/science/article/pii/S0278612520302132?dgcid=author

Attachments:

2021-Event-driven tool condition monitoring methodology.pdf

Pre One:Temporal convolutional network with soft thresholding and attention mechanism for machinery prognostics

Next One:An end-to-end fault diagnostics method based on convolutional neural network for rotating machinery withmultiple case studies