milling
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.
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This dataset is used to develop an algorithm for automatic segmenting the collected signals. 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 segment the recorded signals, a moving window (0.5 sec) is applied to sample the vibration signals and manually labeled the corresponding modes, i.e. dry run or milling, of each window. To verify the algorithm, 3 types of operations are provided and recorded in csv format.
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