Array Pattern Synthesis Using a Digital Position Shift Method

Han, Chuang; Wang, L.

doi:10.13164/re.2016.0573

Cited by 3 publications

(1 citation statement)

References 25 publications

(40 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Z. Hasirci et al [18] applied PSO algorithm to optimize frequency dependent model parameters for different bus bar distribution systems (630, 1250 and 2000 A) and these bus bars functioning as a power line communication at 3-148.5 kHz band were analyzed for frequency and phase shift keying modulations to distinct network alignments. C. Han et al [19] applied Feedback PSO (FPSO) algorithm to minimize the peak side lobe on both digital position shift method and digital position shift with optimal amplitude methods, but the optimized results of both methods shown inferior with other methods reported in the literature particularly steering direction near to end fire direction. E. Tugcu et al [20] used PSO method for blind verification of channel matched filter (CMF) coefficients and shown better performance in terms of bit error rate and mean square error of frequency selective channels with other conventional blind training methods.…”

Section: Introductionmentioning

confidence: 99%

PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization

Meka¹,

Giridhar²,

Sarma³

2018

RADIOENGINEERING

View full text Add to dashboard Cite

Partial discharge (PD) source location using acoustic emission (AE) is widely utilized by many transformer manufacturers and power utility engineers in routine and critical situation for optimal operation of the electrical power system as well as further risk management and repair planning. The PD detection is not enough to take solution, so identification of PD source is essential to restore apparatus condition. This work aim is to localize the defect geometrically by means of TDOA (time difference of arrival) signals from the sensors fixed on the power transformer. The solution for PD source location is acquired by making these nonlinear equations as optimization problem. In this technique, the inertia weight is effectively regulated by using 49 and 9 simple IF-THEN fuzzy rules to improve the global optimal solution and impairs the local convergence problem and improves the accuracy in estimating the PD source location. The simulation results reveal that PD location accuracy with minimum of maximum deviation error, absolute error and relative error is better when compared to other constant parameter intelligent methods which were reported in the literature.

show abstract

Section: Introductionmentioning

confidence: 99%