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FAILURE PROGNOSTICS BY A DATA-DRIVEN SIMILARITY-BASED APPROACH

Abstract : This paper presents a data-driven, similarity-based approach for prognostics of industrial and structural components. The potentiality of the approach is demonstrated on a problem of crack propagation, taken from literature. The crack growth process is described by a non linear model affected by non-additive noises. A comparison is provided with a Monte Carlo-based estimation method, known as particle filtering.
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https://hal-supelec.archives-ouvertes.fr/hal-00926377
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Submitted on : Thursday, January 9, 2014 - 3:03:18 PM
Last modification on : Wednesday, July 15, 2020 - 10:00:02 AM
Long-term archiving on: : Thursday, April 10, 2014 - 9:16:04 AM

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Enrico Zio, F. Di Maio. FAILURE PROGNOSTICS BY A DATA-DRIVEN SIMILARITY-BASED APPROACH. International Journal of Reliability, Quality and Safety Engineering, World Scientific Publishing, 2013, 20, pp.1350001. ⟨10.1142/S0218539313500010⟩. ⟨hal-00926377⟩

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