Development of Acoustic Emission Methods for In-Flight Monitoring of Aircraft Structures

Hutton, P.H.; Lemon, D.K.

doi:10.1007/978-1-4613-3706-5_27

Cited by 4 publications

(1 citation statement)

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“…The difference has become one of nomenclature and the challenges for reliable sensing of damage with statistical performance are very similar regardless of the approach. Neither approach is new, with damage sensing systems being developed within the USAF since the 1930s [3] and concepts for permanently attached sensors being researched in the early 1980s [4] and flown on a fleet of USAF aircraft in the mid to late 1980s [5]. However, even after many years of research and development of technology for new materials and damage types, there remains significant challenges at the foundational level that need to be addressed before damage sensing can meet the desire to have statistically validated capability for aerospace applications that minimize the need for extensive maintenance actions.…”

Section: Damage Sensing Capabilites / Requirementsmentioning

confidence: 99%

USAF Perspective on Foundational Challenges for Enhanced Damage Sensing (Preprint)

Lindgren¹,

Stargel²

2012

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Section: Damage Sensing Capabilites / Requirementsmentioning

confidence: 99%

USAF Perspective on Foundational Challenges for Enhanced Damage Sensing (Preprint)

Lindgren¹,

Stargel²

2012

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Pattern Recognition Analysis of Acoustic Emission Data from 7075-T651 Aluminum Simulated Joint Specimens

Melton

Doctor

Daly

1983

Review of Progress in Quantitative Nondestructive Evaluation

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Classification of NDE Waveforms with Autoregressive Models

Melton

1983

Review of Progress in Quantitative Nondestructive Evaluation

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This paper describes a new approach for classifying NDE waveforms. Using this approach a set of matched filters is constructed, one for each category of waveform, based on parameters from autoregressive models. The method offers advantages in terms of.hardware implementation over conventional pattern recognition approaches. Feasibility is shown using computer generated data. Results are then presented for real data from acoustic emission experiments.

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Development of Acoustic Emission Methods for In-Flight Monitoring of Aircraft Structures

Cited by 4 publications

References 0 publications

USAF Perspective on Foundational Challenges for Enhanced Damage Sensing (Preprint)

USAF Perspective on Foundational Challenges for Enhanced Damage Sensing (Preprint)

Pattern Recognition Analysis of Acoustic Emission Data from 7075-T651 Aluminum Simulated Joint Specimens

Classification of NDE Waveforms with Autoregressive Models

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