An automated feature extraction method with application to empirical model development from machining power data

An automated feature extraction method with application to empirical model development from machining power data

Machining shop floor jobs are rarely optimised for minimisation of the energy consumption, as no clear guidelines exist in operating procedures and high production rates and finishing quality are requirements with higher priorities. However, there has been an increased interest recently in more ener...

Full description

Saved in:
Bibliographic Details
Main Authors: Dimitrios Pantazis, Paul Goodall, Paul Conway, Andrew West
Format: Default Article
Published: 2019
Subjects:
Mechanical engineering not elsewhere classified
Feature extraction
Machining
Hidden Markov model (HMM)
Response Surface Methodology (RSM)
Power data
Time-series segmentation
Energy decomposition
Hierarchical clustering
End-milling
Empirical model
Mechanical Engineering not elsewhere classified
Mechanical Engineering
Online Access:https://hdl.handle.net/2134/36951
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://hdl.handle.net/2134/36951

Similar Items