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Authordc.contributor.authorGriffin, James 
Admission datedc.date.accessioned2015-08-27T18:42:37Z
Available datedc.date.available2015-08-27T18:42:37Z
Publication datedc.date.issued2015
Cita de ítemdc.identifier.citationMechanical Systems and Signal Processing 50-51(2015)757–783en_US
Identifierdc.identifier.otherDOI: 10.1016/j.ymssp.2014.04.018
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/133240
General notedc.descriptionArtículo de publicación ISIen_US
Abstractdc.description.abstractWhen using Acoustic Emission (AE) technologies, tensile, compressive and shear stress/strain tests can provide a detector for material deformation and dislocations. In this paper improvements are made to standardise calibration techniques for AE against known metrics such as force. AE signatures were evaluated from various calibration energy sources based on the energy from the first harmonic (dominant energy band) [1,2]. The effects of AE against its calibration identity are investigated: where signals are correlated to the average energy and distance a the detected phenomena. In addition, extra tests are investigated in terms of the tensile tests and single grit tests characterising different materials. Necessary translations to the time-frequency domain were necessary when segregating salient features between different material properties. Continuing this work the obtained AE is summarised and evaluated by a Neural Network (NN) regression classification technique which identifies how far the malformation has progressed (in terms of energy/force) during material transformation. Both genetic-fuzzy clustering and tree rule based classifier techniques were used as the second and third classification techniques respectively to verify the NN output giving a weighted three classifier system. The work discussed in this paper looks at both distance and force relationships for various prolonged Acoustic Emission stresses. Later such analysis was realised with different classifier models and finally implemented into the Simulink simulations. Further investigations were made into classifier models for different material interactions in terms of force and distance which add further dimension to this work with different materials based simulation realisations. Within the statistical analysis section there are two varying prolonged stress tests which together offer the mechanical calibration system (automated solenoid and pencil break calibration system). Taking such a mechanical system with the real-time simulations gives a fully automated accurate AE calibration system to force and distance measurement phenomena.en_US
Lenguagedc.language.isoenen_US
Publisherdc.publisherElsevieren_US
Type of licensedc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
Keywordsdc.subjectSingle grit scratch testsen_US
Keywordsdc.subjectEmisión acústicaen_US
Keywordsdc.subjectForceen_US
Keywordsdc.subjectTime–frequency domainen_US
Keywordsdc.subjectTensile testsen_US
Keywordsdc.subjectSignal analysisen_US
Keywordsdc.subjectNeural networksen_US
Keywordsdc.subjectFuzzy-c clusteringen_US
Keywordsdc.subjectCART rule based system and Simulinken_US
Keywordsdc.subjectModelsen_US
Títulodc.titleTraceability of Acoustic Emission measurements for a proposed calibration method - Classification of characteristics and identification using signal analysisen_US
Document typedc.typeArtículo de revista


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Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 Chile