Automatic Classification of Transmission Line Faults Using Probabilistic Neural Network and Discrete Wavelet Transform

Abstract

The largest physical length of transmission network is the most critical part of the power system. The fast recognition of faults and events in transmission line has a significant role in order to prevent equipment damage and suddenly collapse of power system. The signal-processing and computational-intelligence based techniques have been proposed in literature for automatic classification of faults and events in transmission network. In this paper, discrete wavelet transform based probabilistic neural network have been proposed for the identification and classification of faults in transmission network. The short circuit faults are created at various fault resistances and fault locations. The wavelet transform is used to extract the features in order to distinguish the type of faults. The probabilistic neural network is used to automatically classify the type of faults. A real-time transmission network is used for simulation of faults. The simulation results show that the proposed algorithm is efficient and reliable for automatic classification of faults in electrical power system.

Authors and Affiliations

Suhail Khokhar, Suhail Mustafa, Adnan Ahmed Arain, Mohsin Ali Tunio

Keywords

Related Articles

Authorized Public Auditing of Dynamic Storage on Cloud with Efficient Verifiable Fine-Grained Updates with MHT

One of the top technology concept is Cloud Computing. Cloud storage servers plays an important role in the technology buzz – cloud computing where clients can store their data at cloud servers and can access this data f...

Design and Implementation of Pyramidal Horn Antenna

This technical paper presents design and implementation of pyramidal horn antenna. Antenna is a transducer used to convert electrical signals into electromagnetic waves i.e. radio waves. Horn antenna supports wide range...

Heat Transfer Analysis by CFD Simulation for Different shapes of Fins

An air-cooled motorcycle engine releases heat to the atmosphere through the mode of forced convection to facilitate this, fins are provided on the outer surface of the cylinder. The heat transfer rate depends upon the v...

slugStudy o f Re lationship Between Utilitarian and Hedonic Motives and Temporal Perspective a t Retail Malls

The paper examines the relationship between youth shopping motives and timing of shopping for home furniture. The age group selected is 18 to 29 years. The shopping motives considered for study are uti...

Multi-objective Thermal Power Scheduling by Evolutionary Search Weighted Simulation Techniques

In the present paper multi-objective thermal power dispatch problem with three objectives and constrains has been addressed. The multi-objective economic-emission dispatch problem is converted into a scalar optimization...

Download PDF file
  • EP ID EP24360
  • DOI -
  • Views 310
  • Downloads 8

How To Cite

Suhail Khokhar, Suhail Mustafa, Adnan Ahmed Arain, Mohsin Ali Tunio (2017). Automatic Classification of Transmission Line Faults Using Probabilistic Neural Network and Discrete Wavelet Transform. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(5), -. https://www.europub.co.uk/articles/-A-24360