Expert system for classification and analysis of power system events

Classification of power quality events – A review

“…In [96], researchers presented a fuzzy expert system based on features extracted from both Fourier Transform (FT) and WT for synthetic without noise PQ data classification. In [82], authors suggested an expert system that was able to classify different types of power system events to the underlying causes and offer useful information in terms of PQ. In [97], authors presented a fuzzy expert system based classification system.…”

“…In [71], HT and Clarke Transform (CT) for FE and K-nearest Neighbor (k-NN) technique for classification have been used. Several other techniques such as Hilbert Transform (HT) [72], Time-Time Transform [73], HOS method [74,75], Hyperbolic S-transform [66], Kalman filtering [76][77][78], Multi-way Principal Component Analysis (MW-PCA) [79], Adaline method [80], EMDRA method [81], Kalman filtering [82,83], Hidden Markov Model [84], and Fractal-based method [85] have played significant role for PQ events classification in the past years.…”

Classification of power system disturbances using linear Kalman filter and fuzzy-expert system

“…Expert systems have been proposed to identify, classify and diagnose power system events successfully for a limited number of events [24][25][26][27]. Rules based expert systems are highly dependent on if .…”

Spike Detection of Disturbed Power Signal Using VMD

“…Now-a-days most of the equipments such as programmable logic controllers, computer terminals, home appliances, diagnostic systems etc are quite susceptible to power disturbance such as impulsive and oscillatory transients, harmonics, notching, voltage sags, voltage swells, and the power interruptions [1][2][3][4][5][6][7][8][9][10][11] . All these disturbances reduce the quality of service and raise the failure rates.…”