2002
DOI: 10.1049/pe:20020603
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Intelligent condition monitoring and asset management. Partial discharge monitoring for power transformers

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Cited by 55 publications
(30 citation statements)
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“…Various techniques, such as ultra high frequency (UHF) signal detection [3], acoustic emissions detection [4] and dissolved gas analysis [4], have been proposed as means of monitoring partial discharge activity within transformers. All of the above rely on sensors gathering data that can be used to identify the occurrence of unusual activity within the transformer.…”
Section: Introductionmentioning
confidence: 99%
“…Various techniques, such as ultra high frequency (UHF) signal detection [3], acoustic emissions detection [4] and dissolved gas analysis [4], have been proposed as means of monitoring partial discharge activity within transformers. All of the above rely on sensors gathering data that can be used to identify the occurrence of unusual activity within the transformer.…”
Section: Introductionmentioning
confidence: 99%
“…Judd et al [40] describe a MAS-based four-layer architecture, with the objective of monitoring the power transformers by using the ultra-high frequency of partial discharge (UHFoPD) as a monitoring parameter. The framework in Table 3 illustrates that the baseline technology constitutes the multi-agent system for the power industry.…”
Section: Condition Monitoring and Diagnosticsmentioning
confidence: 99%
“…Its operation is explained. The COMMAS of Judd et al [40] has been modified to add two more agents in the interpretation layer.…”
Section: Condition Monitoring and Diagnosticsmentioning
confidence: 99%
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“…arious techniques, such as ultra high frequency (UHF) signal detection [3], acoustic emissions detection [4] and dissolved gas analysis [4], have been proposed as means of monitoring partial discharge activity within transformers. All of the above rely on sensors gathering data that can be used to identify the occurrence of unusual activity within the transformer.…”
Section: Introductionmentioning
confidence: 99%