MARC details
| 000 -LEADER |
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| fixed length control field |
02100nam a2200289Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
MX-MdCICY |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250625162445.0 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
CICY |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
B-20261 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250602s9999 xx |||||s2 |||| ||und|d |
| 245 10 - TITLE STATEMENT |
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| Title |
Intelligent structural health monitoring of composite structures using machine learning, deep learning, and transfer learning: a review |
| 490 0# - SERIES STATEMENT |
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| Volume/sequential designation |
Advanced Composite Materials, 33(2), p.162-188, 2023 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
Structural health monitoring (SHM)methods are essential to guarantee the safety and integrity of composite structures, which are extensively utilized in aerospace, automobile, marine, and infrastructure industry. The deterioration of composite structures is primarily caused by operational and environmental variability. To address this issue, artificial intelligence (AI)techniques are being integrated into the SHM systems to enhance the performance of composite structures via digital transformation and big data analysis. Therefore, the present article aims to provide a critical review of AI models, including machine learning, deep learning, and transfer learning, to preserve and sustain composite structures throughout their life. The article covers the complete SHM process for composite structures, including sensing technologies, data-preprocessing, feature extraction, and decision-making process. Thus, the health monitoring of composites is presented in consideration of modern AI techniques, accompanied by the identification of current challenges and potential future research directions. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
ARTIFICIAL INTELLIGENCE |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
STRUCTURAL HEALTH MONITORING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPOSITE STRUCTURES |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
MACHINE LEARNING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
DEEP LEARNING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
TRANSFER LEARNING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
DAMAGE DETECTION |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Azad, M. M. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Kim, S. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Cheon, Y. B. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Kim, H. S. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="https://drive.google.com/file/d/1vNL32cmucHjJJ799KqWp-utL6x-d_xFF/view?usp=drivesdk">https://drive.google.com/file/d/1vNL32cmucHjJJ799KqWp-utL6x-d_xFF/view?usp=drivesdk</a> |
| Public note |
Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Clasificación local |
| Koha item type |
Documentos solicitados |
