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. 2021 Apr 30;21(9):3137. doi: 10.3390/s21093137
SVM Support vector machine
TCM Tool condition monitoring
MCU Microcontroller
ML Machine learning
RF Random forest
RBF Radial Basis Function
MAPE Mean absolute percentage error
L&T Longitudinal and torsional composite vibrational mode
CAD Computer aided design
Lf Free length of the end mill (mm)
FEM Finite element method
PZT Piezoelectric transducer
OD Outer diameter (mm)
ID Inner diameter (mm)
H Height (mm)
PCBA Printed circuit board assembly
MCU Microcontroller
DC Direct current
3D Three dimensional
CNC Computerized numerical control
HSS High speed steel
n Spindle speed (RPM)
vf Feed seed (mm/min)
fz Feed per tooth (mm/tooth)
ap Axial depth of cut (mm)
ae Radial depth of cut
uK, uN node displacement vectors
M Mass matrix
K Stiffness matrix
C Damping matrix
α Mass proportional damping coefficient
β Stiffness proportional damping coefficient
C Carbon (%)
Si Silicon (%)
Mn Manganese (%)
Ni Nickel (%)
P Phosphorus (%)
S Sulfur (%)
Cr Chromium (%)
Mo Molybdenum (%)
Ra Arithmetic mean roughness (µm)
Avg Average value of the capacitor charge level values
Var Variability value of the capacitor charge level values
Sd Standard deviation of the capacitor charge level values
ACorr Autocorrelation value of the capacitor charge level values
M 4 Avg 4 data point simple moving averages of the capacitor charge level
InterQ Interquartile value of the capacitor charge level values
Energy Absolute energy of the capacitor charge level values
ACF Autocorrelation function
MAF Moving average formula
k Time interval
Q Quantile function
Q 1 First quartile
Q 4 Fourth quartile
p Probability value (0 < p < 1)
r Negative correlation
R2 Coefficient of determination (0 < R2 ≤ 1)
SSR Sum of squares of residuals
SST Total sum of squares
yi^ The predicted value
y¯ The mean value
PtoP Peak-to-peak
MAPE The root mean square error
STDL Seasonal-Trend decomposition by losses
Tt Trend component
St Seasonal component
Rt Irregular
SE Shannon entropy
f^λ Estimate of the spectral density of data