Precognitive maintenance and probabilistic assessment of tool wear using particle filters
10.1109/IECON.2013.6700361
Saved in:
Main Authors: | Yan, H.-C., Pang, C.K., Zhou, J.-H. |
---|---|
Other Authors: | ELECTRICAL & COMPUTER ENGINEERING |
Format: | Conference or Workshop Item |
Published: |
2014
|
Online Access: | http://scholarbank.nus.edu.sg/handle/10635/84109 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
PDF and breakdown time prediction for unobservable wear using enhanced particle filters in precognitive maintenance
by: Pang, Chee Khiang, et al.
Published: (2016) -
PROBABILISTIC FAULT DIAGNOSIS AND PROGNOSIS IN PRECOGNITIVE MAINTENANCE FOR HIGH-PERFORMANCE MANUFACTURING INDUSTRIES
by: YAN HENGCHAO
Published: (2017) -
A mixed time-/condition-based precognitive maintenance framework using support vectors
by: Pang, C.K., et al.
Published: (2014) -
Tool wear forecast using Dominant Feature Identification of acoustic emissions
by: Pang, C.K., et al.
Published: (2014) -
Intelligent Diagnosis and Prognosis of Tool Wear Using Dominant Feature Identification
by: Zhou, J.-H., et al.
Published: (2014)