Fast Fourier Transform Analysis on: Parks and Extended Parks Quantity

 Extended Park Vector Approach and 15 Statistical Features

The EPVA method works by converting the three-phase currents (i_sa, i_sb, i_sc) into direct and quadrature axis (id and iq)  and it finds the modulus id + jiq (ip) of   as follows [1]:

Note: Sample length = 100 samples

          Overlap = 65 samples

 Fast Fourier Transform (FFT) analysis: Characteristic Fault Frequencies (CFFs)

0.3% fault at no load and 100% load

(a)

0.7% fault at no load and 100% load

(b)

Figure 1: Frequency response at no load and 100% load condition, (a)  for 0.3% severity and (b) 0.7% severity

 

1.05% fault at no load and 100% load

(a)

2.1% fault at no load and 100% load

(b)

Zoom view of the Parks quantity

(c)

Figure 2: Frequency response at no load and 100% load condition, (a)  for 1.05% severity, (b) 2.1% severity and (c) zoom view of id, and iq .

Reference

[1]  Kumar, R., Cirrincione, G., Cirrincione, M., Tortella, A. and Andriollo, M., 2021. Induction Machine Fault Detection and Classification Using Non-Parametric, Statistical-Frequency Features and Shallow Neural Networks. IEEE Transactions on Energy Conversion, 36(2), pp.1070-1080.