Pattern Recognition System For Condition Monitoring Of Overhead Power Distribution Line Insulators Using Curvelet and Contourlet Features

Volume 5 Issue 1 March - May 2018

Research Article

Pattern Recognition System For Condition Monitoring Of Overhead Power Distribution Line Insulators Using Curvelet and Contourlet Features

Potnuru Surya Prasad*, Bhima Prabhakara Rao**

*Ph.D Scholar, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

**Programme Director, School of Nanotechnology, JNTU, Kakinada, Andhra Pradesh, India.

Prasad, P.S., and Rao, B.P., (2018). Pattern Recognition System For Condition Monitoring Of Overhead Power Distribution Line Insulators Using Curvelet And Contourlet Features. i-manager’s Journal on Pattern Recognition, 5(1), 21-31. https://doi.org/10.26634/jpr.5.1.14792

Abstract

The power distribution system is considered as the important component of a power system because the consistent delivery of power to the consumers depends on it. Due to massive growth in the consumption of power, the damaged insulators on the electric poles prompt the breakage of the power supply which leads to considerable loss occurring for the power industry and hence to the national economy. As the insulators protect the power distribution system from heavy transients, there must be a monitoring system to regularly check the condition of the insulators. Regular monitoring of the overhead power line insulators requires taking pictures of the poles, sending them to the processing unit and applying image processing techniques to classify the insulator health condition into either healthy or risky and subsequent necessary replacement of the damaged insulator can be done by the maintenance personnel. Using the above procedure, the breakage condition of the insulators can be determined. The insulator images are extracted from the acquired pole image input and then individual insulator's statistical features are obtained based on curvelet transform and contourlet transform coefficients. The obtained features of insulator images are given to SVM (Support Vector Machines) classifier in determining the health condition of an insulator and the experiment results are validated. The health condition monitoring of power system insulators can be done reliably and hence this method of automatic classification would reduce the human efforts to a greater extent.