This dataset is used to develop an algorithm for evaluating machining quality. When machining a workpiece in a milling process, vibration signals can be recorded by a 3-axis accelerometer, which is attached on the spindle of a CNC milling machine. To evaluate machining quality, the vibration signals can be segmented and extracted the corresponding features, in the time, frequency, and time-frequency domains. After serving with the features, a model can be developed to estimate the machining quality, such as the roughness of a workpiece.

Dataset Files

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[1] Haw-Ching Yang, "Roughness of Milling Process", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/rx49-xs81. Accessed: Apr. 13, 2024.
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doi = {10.21227/rx49-xs81},
url = {http://dx.doi.org/10.21227/rx49-xs81},
author = {Haw-Ching Yang },
publisher = {IEEE Dataport},
title = {Roughness of Milling Process},
year = {2020} }
TY - DATA
T1 - Roughness of Milling Process
AU - Haw-Ching Yang
PY - 2020
PB - IEEE Dataport
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Haw-Ching Yang. (2020). Roughness of Milling Process. IEEE Dataport. http://dx.doi.org/10.21227/rx49-xs81
Haw-Ching Yang, 2020. Roughness of Milling Process. Available at: http://dx.doi.org/10.21227/rx49-xs81.
Haw-Ching Yang. (2020). "Roughness of Milling Process." Web.
1. Haw-Ching Yang. Roughness of Milling Process [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/rx49-xs81
Haw-Ching Yang. "Roughness of Milling Process." doi: 10.21227/rx49-xs81