| 000 | 02395nam a2200301Ia 4500 | ||
|---|---|---|---|
| 003 | MX-MdCICY | ||
| 005 | 20250625164352.0 | ||
| 040 | _cCICY | ||
| 090 | _aB-21306 | ||
| 245 | 1 | 0 | _aArtificial intelligence in real-time diagnostics and prognostics of composite materials and its uncertainties - A review |
| 490 | 0 | _aSmart Materials and Structures. 30(8), 83001, 2021, DOI: 10.1088/1361-665X/ac099f | |
| 520 | 3 | _aIn the era of the 4th industrial revolution of big data, artificial intelligence (AI) is widely used in each and every field of composite materials which includes design and analysis, material storage, manufacturing, non-destructive testing, structural health monitoring (SHM) and prognostics of its remaining useful life, material state (MS) and damage modes. While these AI models are rapidly developed and integrated into the industrial internet of things to keep track of the health of a composite material from its birth to death, these integrations remain uncertain for prognostics without the certainty of its previous MS. This article is a comprehensive review of the AI models being developed over the past few decades in the field of SHM and prognostics health management of polymer matrix composites. It further analyzes the real gaps between these developments and the nature of uncertainty of these methods. Finally, the pipeline for the real-time prognostics from birth to death, hybrid approaches, uncertainty quantification of data-driven and physics-based systems, and its reliability standards to such complex advanced composite materials are discussed. This paper will be focused as a basic guide for researchers implementing AI in composites for diagnosis, prognosis, and control. © 2021 IOP Publishing Ltd. | |
| 650 | 1 | 4 | _aARTIFICIAL INTELLIGENCE |
| 650 | 1 | 4 | _aCOMPOSITE MATERIALS |
| 650 | 1 | 4 | _aCONDITION BASED MAINTENANCE |
| 650 | 1 | 4 | _aDAMAGE |
| 650 | 1 | 4 | _aMACHINE LEARNING |
| 650 | 1 | 4 | _aPROGNOSTICS HEALTH MANAGEMENT |
| 650 | 1 | 4 | _aSTRUCTURAL HEALTH MONITORING |
| 700 | 1 | 2 | _aElenchezhian M.R.P. |
| 700 | 1 | 2 | _aVadlamudi V. |
| 700 | 1 | 2 | _aRaihan R. |
| 700 | 1 | 2 | _aReifsnider K. |
| 700 | 1 | 2 | _aReifsnider E. |
| 856 | 4 | 0 |
_uhttps://drive.google.com/file/d/1BgzQLbZrCpm8arOnY9gH3ySepilz3P3g/view?usp=drivesdk _zPara ver el documento ingresa a Google con tu cuenta @cicy.edu.mx |
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