Table 7.

Data-driven FDD application examples in sensors.

Ref.	Faulty Event	Meas. Signal	Feat. Sel./Extr.	Algorithm	Data Source
[190]	Bias and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	-	MPCA	Test-bench
[186]	Stuck, noise and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	-	Extreme Learning Machine	Simu. and Test-bench
[191]	Generic faults	$i_{\mathrm{abc}}$	t-domain	ANN	Simu. and Test-bench
[192]	Bias and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$ and $T_{\mathrm{em}}$	CCA and KLD	CNN	Test-bench
[185]	Bias and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	PCA	SVM	Simu. and Test-bench
[184]	Bias and ramp	$i_{\mathrm{abc}}$	PCA and KLD	ANN	Test-bench
[193]	Ramp, stuck and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	-	DeepPCA	Test-bench
[187]	Generic faults	$i_{\mathrm{abc}}$ an $\omega$	PCA	ANN and kNN	Simu.
[194]	Bias and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	-	PCA	Test-bench
[188]	Generic faults	Strain gauge	-	kNN	Real data
[189]	Generic faults	Temperature	t-domain	SVM	Simu.
[195]	Generic faults	$v_{\mathrm{abc}}$ and $v_{\mathrm{dc}}$	-	Extreme Learning Machine	Test-bench
[196]	Stuck, noise, gain and offset	$i_{\mathrm{abc}}$, $\omega$ and $v_{\mathrm{dc}}$	t and f-domain	Extreme Learning Machine	Simu. and Test-bench