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
1 and
2 form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed.
Detection of fluid leaks in pipe-type cable installations is important for both environmental and operational reasons. A new application of modern numerical algorithms, such as neural and ...probabilistic networks, for monitoring pressure system installations has been recently presented by the authors. This approach led to the development of a complete system for monitoring high-pressure, fluid-filled cables. During the initial system implementation, a need arose for the detection of very small leaks. To meet this need, the detection algorithms were revised and new features were implemented. This paper describes the new algorithms and discusses their implementation.
This article covers the topic of designing the operational amplifiers, it describes the design of a compact, low power amplifier utilizing 0.35 μm CMOS technology. The main motivation behind this ...work was the existing need at the Technical University of Lodz for compact device that could be easily employed in larger designs. This article describes best topology for each stage in terms of meeting the design goals. The final circuit is a unique combination of low power topologies with solutions from large gain, high power amplifiers. This was done to achieve largest possible value of amplifier's gain within total power consumption constraint. The device performance was verified positively both at the schematic and at the layout level.
This paper discusses application of continuous probabilistic networks to leak detection in high-pressure, fluid-filled (HPFF) cables. An existing system for leak detection, build on discrete network, ...has a number of drawbacks - mainly the probability specification is difficult and quantization of input data has to be performed. An approach using continuous functions is proposed in the paper, which overcomes some restrictions of continuous probabilistic networks found in the literature. It introduces an algorithm for efficient utilization of the nonlinear functions in continuous networks. The existing discrete network, for assessing leak probability, is replaced with a continuous one. Number of tests is performed to verify operation of the leak detection system with the new network type.
