Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2019.1565337
Robust detection of real-time power quality disturbances under noisy condition using FTDD features
O. Jeba Singh
; Department of EEE, Arunachala College of Engineering for Women, Vellichanthai, Tamil Nadu, India
D. Prince Winston
; Department of EEE, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India
B. Chitti Babu
; Department of EEE, The University of Nottingham(U.K), Selangor, Malaysia
S. Kalyani
; Department of EEE, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India
B. Praveen Kumar
; Department of EEE, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India
M. Saravanan
; Department of EEE, Thiagarajar College of Engineering, Madurai, Tamil Nadu, India
S. Cynthia Christabel
; Department of ECE, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India
Sažetak
To improve power quality (PQ), detecting the particular type of disturbance is the foremost thing before mitigation. So monitoring is needed to detect the PQ disturbance that occurs in a short duration of time. Classification of real-time PQ disturbances under noisy environment is investigated in this method by selecting an appropriate signal processing tool called fusion of time domain descriptors (FTDD) at the feature extraction stage. It’s a method of extracting power spectrum characteristics of various PQ disturbances. Few advantages like algorithmic simplicity and local time-based unique features makes the FTDD algorithm ahead of other techniques. PQ events like voltage sag, voltage swell, interruption, healthy, transient and harmonics mixed with different noise conditions are analysed. multiclass support vector machine and Naïves Bayes (NB) classifiers are applied to analyse the performance of the proposed method. As a result, NB classifier performs better in noiseless signal with 99.66%, wherein noise added signals both NB and SVM are showing better accuracy at different signal to noise ratios. Finally, Arduino controller-based hardware tool involved in the acquisition of real-time signals shows how our proposed system is applicable for industries that make detection simple.
Ključne riječi
Power quality; fusion of time domain descriptors: signal to noise ratio; multi support vector machine; Naives Bayes
Hrčak ID:
239750
URI
Datum izdavanja:
26.2.2019.
Posjeta: 679 *