This document proposes the utilization of partial discharge (PD) optical signals from a fluorescence optical sensor system for constructing φ-u-n charts and gray-scale images. The fractal characteristics cannot fully characterize the PD gray-scale images, which reduce the PD pattern recognition rates. Multifractal spectrum is used for analyzing the characteristics of gray-scale images, and a new probability calculation method is proposed for computing the multifractal spectrogram of these images. By conducting a series of experiments, the multifractal spectrum is proven effective in describing the variations in the geometric characteristics of the gray-scale images. The main physical features of the multifractal spectrum are extracted and used as pattern recognition features. The backpropagation neural network with an improved conjugate gradient algorithm is used as a classifier in identifying the different PD types, which achieves recognition rates that are >87%. The multifractal spectrum improves the accuracy of the PD pattern recognition unlike other pattern recognition features, such as the box-counting dimension and the information dimension.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.