&lt;title&gt;Source location of acoustic emissions from atmospheric leakage using neural networks&lt;/title&gt;

Barga, Roger; Friesel, Mark A.; Meador, J.

doi:10.1117/12.44993

“…The importance of leak source location led two of the authors to examine a neural network approach [4], utilizing data obtained in the laboratory from a ribbed aluminum plate. A two-sensor array was used to record air jet acoustic emissions on a plate section previously used…”

Section: Neural Network Approach To Leak Locationmentioning

confidence: 99%

Acoustic emissions applications on the NASA space station

Friesel

¹

,

Barga

²

,

Dawson

³

et al. 1993

NDT & E International

0

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Acoustic emission is being investigated as a way to continuously monitor the space station Freedom for damage caused by space debris impact and seal failure. Experiments run to date focused on detecting and locating simulated and real impacts and leakage. These were performed both in the laboratory on a section of material similar to a space station shell panel and also on the full-scale common module prototype at Boeing's Huntsville facility. A neural network approach supplemented standard acoustic emission detection and analysis techniques.

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“…The importance of leak source location led two of the authors to examine a neural network approach [4], utilizing data obtained in the laboratory from a ribbed aluminum plate. A two-sensor array was used to record air jet acoustic emissions on a plate section previously used 60 80 100 120 140 160 180 SensorDistancelrom Leak, in.…”

Section: Neural Network Approach To Leak Locationmentioning

confidence: 99%

Acoustic Emissions Applications on the Nasa Space Station

Friesel

¹

,

Barga

²

,

Dawson

³

et al. 1992

Review of Progress in Quantitative Nondestructive Evaluation

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show abstract

“…The importance of leak source location led two of the authors to examine a neural network approach [4], utilizing data obtained in the laboratory from a ribbed aluminum plate. A two-sensor array was used to record air jet acoustic emissions on a plate section previously used elsewhere for impact tests.…”

Section: Neural Network Approach To Leak Locationmentioning

confidence: 99%