Dataset for Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous framework
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下载链接：
https://zenodo.org/record/10441304
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资源简介：
This is the dataset related to the publication titled:
Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous frameworkPublished in the journal Eksploatacja i Niezawodność – Maintenance and Reliability DoI: 10.17531/ein/178274
The training and test data have been uploaded in sets of 5000 data points each in form of a structure named cases or A and numbered from 111-117The number and the tool condition are in the table below
111
Normal insert with no defects
TN
112
Wear at flank face
TWFC
113
Wear at nose radius
TWNSR
114
Notch wear
TWNT
115
Crater wear
TWCT
116
Fracture of cutting edge
TFCE
117
Built-up cutting edge
TBUE
创建时间：
2024-02-19
