Novel Leak Detection System for Pipe Type Cable Installations

Tylman, Wojciech; Anders, G.J.; Ghafurian, R.

doi:10.1109/tpwrd.2006.874657

Cited by 9 publications

(12 citation statements)

References 3 publications

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“…Unfortunately, many factors prevent us from using such an analytic solution in a straightforward way: temperature may not be equal throughout the whole installation, it may be difficult to account for volume changes, sensors may give inaccurate results, the properties of the liquids may not be known exactly and may change in time. For these reasons, another approach has been described in [1]. The system uses three separate algorithms that try to compute one measurable quantity of the pressurized system -the output -on the basis of other selected measurable quantities -the inputs.…”

Section: A Leak Detection Principlementioning

confidence: 99%

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Application of continuous probabilistic networks to leak detection in pipe-type cable installations

Kolczynski

Tylman

Anders

2010

2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems

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This paper discusses application of continuous probabilistic networks to leak detection in high-pressure, fluidfilled (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.

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Section: A Leak Detection Principlementioning

confidence: 99%

“…In [1] the authors presented a system for leak detection in HPFF power cables, utilizing discrete probabilistic network. This approach has its disadvantages that can be removed by application of a continuous probabilistic network.…”

Section: Introductionmentioning

confidence: 99%

Application of continuous probabilistic networks to leak detection in pipe-type cable installations

Kolczynski

Tylman

Anders

2010

2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems

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“…The methodology developed by the authors and presented in [1] and [2] uses an expert system employing neural and probabilistic networks for detection of dielectric fluid leaks. Section II briefly reviews the philosophy behind the original approach, describes the main module for modeling the pressure-temperature relationship, and provides an overview of the probabilistic network as a decision-making tool.…”

Section: P Ipe-type Cable Installations Can Be Found In Most Largementioning

confidence: 99%

“…All such problems have to be eliminated before other actions are taken. Details of the filtering stage are given in [1].…”

Section: Data Pathmentioning

confidence: 99%

“…The HPFF cables leak detection system described in [1] relies on three separate markers: 1) a pressure calculation marker that relates the changes in the liquid pressure to the temperature and electric current changes; 2) a pump operation marker that counts the number of the pressurizing pump operations; and 3) a valve operation marker that monitors the operation of the pressure relief valve. The first marker is modeled using a neural network (described further in this paper), and the last two are heuristic models, described in [1].…”

Section: Data Pathmentioning

confidence: 99%

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Detecting Small Fluid Leaks in Pipe-Type Cable Installations

Kolczynski

Tylman

Anders

2010

IEEE Trans. Power Delivery

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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 highpressure, 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.Index Terms-Dielectric fluid leak detection, neural networks, pipe-type cables, probabilistic networks.

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Application of probabilistic networks for decision support in power system analysis

Tylman¹,

Anders²

2006

Energy

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Novel Leak Detection System for Pipe Type Cable Installations

Cited by 9 publications

References 3 publications

Application of continuous probabilistic networks to leak detection in pipe-type cable installations

Application of continuous probabilistic networks to leak detection in pipe-type cable installations

Detecting Small Fluid Leaks in Pipe-Type Cable Installations

Application of probabilistic networks for decision support in power system analysis

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