Windowing Based Continuous S-Transform (ST) with Deep Learning for Detection and Classifying Power Quality Disturbances (PQDs) | Chapter 07 | Technological Innovation in Engineering Research Vol. 2

 For interrupt and transient disturbance detection and classification, transform (ST) using a deep learning classifier. Interruption is a sort of power quality disruption (PQ). The major purpose is to use ST as a signal processing approach to investigate the detection and classification of voltage interrupts and transients. Half-cycle and one-cycle windowing methods (WT) are the two types of windowing techniques that are used for comparison. The disturbance signal was created using the MATLAB computer language and stored as an m-file. ST was used to extract the relevant feature in the form of scattering data from the disturbance signal. Within the disturbance signal, the scattering data was then employed to establish a detection interface. The data from the scattering is sent into a neural network (NN) that classifies it. The % accuracy of the disturbance signal. This research presents a windowing approach for power quality disturbance classification that may provide smooth detection and suitable features for high accuracy percentages (PQDs).

Author(S) Details

K. Daud
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

M. B. M. Mansor
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

Z. H. Che Soh
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

A. A. Abd Samat
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

M. A. Shafie
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

A. P. Ismail
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.

M. H. Abdullah
Faculty of Electrical Engineering, Cawangan Pulau Pinang, [Universiti Teknologi MARA] 13500 Permatang Pauh, Pulau Pinang, Malaysia.


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