Machine Learning in Vibration Control, Vibration Energy Harvesting, and Structural Health Monitoring: A Review
Artykuł przeglądowy (review)
MNiSW
100
Lista 2024
| Status: | |
| Autorzy: | Du Houfan , Duan Bohao, Huang DongMei, Wang Lu, Litak Grzegorz, Xu Haitao , Zhou ShengXi, Jiang Zhuangde |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2026 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 15 |
| Wolumen/Tom: | 26 |
| Strony: | 21965 - 22011 |
| Impact Factor: | 4,5 |
| Scopus® Cytowania: | 0 |
| Bazy: | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| With the widespread adoption of sensors, research into vibration control (VC), vibration energy harvesting (VEH), and structural health monitoring (SHM) has garnered growing attention. However, conventional methods in these fields struggle with high- dimensional, multisource data processing, while machine learning (ML) has emerged as a promising solution for handling nonlin- ear, complex vibration-related data and enabling real-time data analysis. Existing reviews typically focus on ML applications in a single domain, lacking a cross-field synthesis. This review com- prehensively summarizes the latest ML advances in VC, VEH, and SHM. For VC, it addresses the challenge of adapting to dynamic operational conditions and outlines prospects of adaptive control via reinforcement learning (RL). For VEH, it targets unstable energy conversion under random ambient vibrations and highlights optimized harvesting strategies using deep learning. For SHM, it tackles microdamage feature masking by environmental interference and envisions improved detection via computer vision models. It further analyzes domain- specific ML challenges and emerging research directions, providing readers with a unified cross-field framework, clear technical bottleneck insights, and actionable guidance for advancing intelligent vibration-related engineering systems. |
