tool wear dataset

Yingguang, LI

Description

This dataset is used for i) analyzing the influence of process information on monitoring signals through signal processing methods; ii) training and testing models of tool monitoring and tool wear prediction especially for cutting conditions with large variations including cutting parameters, material and geometry of cutting tools, and workpiece materials, and also cutting conditions with continuous changes. This data set includes monitoring signals collected from machining process of sidewalls and closed pockets. The sidewall machining belongs to the cutting process with fixed cutting conditions; the closed pocket machining belongs to the cutting process of continuously varying cutting conditions for the reason that the tool path of closed pocket includes line, arc, full cutting and non-full cutting. Although cutting parameters are given fixed in the arc tool path area, the actual cutting parameters (such as feed, cutting width) are constantly changing due to the change of cutting geometry.

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.8

FAIR Score

58%

Citations

3

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

IEEE DataPort

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Mechanical Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

58%

Source

Scholar Data Model

Keywords

Artificial IntelligenceMechanical SensingSignal ProcessingDigital signal processingtool wearcutting forceVibrationspindle current and powervariable cutting condition

Normalization Factors

FT

53.85

CTw

1.00

MTw

1.00