1. Fully automatic AI-based leak detection system
- Author
-
Tylman, Wojciech, Kolczyński, Jakub, and Anders, George J.
- Subjects
- *
DIELECTRICS , *GAS leakage , *BAYESIAN analysis , *DECISION making , *ARTIFICIAL neural networks , *ARTIFICIAL intelligence , *AUTOMATIC machinery - Abstract
Abstract: This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network – the decision-making component of the system – using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in and form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed. [ABSTRACT FROM AUTHOR]
- Published
- 2010
- Full Text
- View/download PDF