A Novel Hybrid Transform approach with integration of Fast Fourier, Discrete Wavelet and Discrete Shearlet Transforms for prediction of surface roughness on machined surfaces

•A novel hybrid shearlet application to characterize the surface integrity is proposed.•Integrated Fourier-Wavelet-Shearlet transform is used for predicting surface roughness.•Prediction error of MLFFANN training with cutting and vision parameters is less.•Validation roughness error of proposed meth...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Measurement : journal of the International Measurement Confederation Jg. 164; S. 108011
Hauptverfasser:	Prabhakar, D.V.N., Sreenivasa Kumar, M., Gopala Krishna, A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Elsevier Ltd 01.11.2020 Elsevier Science Ltd
Schlagworte:	Aluminum Artificial neural networks Cutting parameters Directional sensitivity Discrete element method Discrete Wavelet Transform End milling Experimentation Fast Fourier transformations Fourier transforms High speed tool steels Hybrid transform Machine vision Neural networks Numerical controls Orthogonal arrays Shearlets Studies Surface roughness Wavelet transforms Hybrid transform Surface roughness Machine vision Artificial neural networks Shearlets
ISSN:	0263-2241, 1873-412X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!