Structural Prognostics and Health Management in Power & Energy Systems

• Autore: Wang Dong
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 online resource (218 p.)
• Soggetto topico: Philosophy
• Soggetto non controllato: analysis mode decomposition; analysis-empirical mode decomposition; data-driven; deep learning; DNN; dynamic analysis; dynamic analysis of the structure; dynamic fuzzy reliability analysis; empirical mode decomposition; extremum surface response method; fault detection; full-scale static test; fuzzy safety criterion; health monitoring; lateral-river vibration; life cycle cost; lithium-ion battery; low frequency tail fluctuation; machine learning; mode mixing; multioperation condition; NAR neural network; neural networks; non-probabilistic reliability index; offshore structures; offshore wind turbines; oil and gas platforms; operational modal analysis; optimized deep belief networks; probabilistic analyses of stochastic processes and frequency; prognostic and Health Management; prognostics; regeneration phenomenon; reliability; remaining useful life; renewable energy; residual useful life; retrofitting activities; rotation of hydraulic generator; sensitivity analysis; sifting stop criterion; similarity-based approach; stochastic subspace identification; strain prediction; structural health monitoring; supervisory control and data acquisition system; supporting vector machine (SVM); techno-economic assessments; turbine blisk; underground powerhouse; vertical axis wind turbine; vibration test; vibration transmission mechanism; wave-structure interaction (WSI); wavelet decomposition; weighted regression; wind and wave analysis; wind turbine blade; wind turbines
• Persona (resp. second.): ZhangXiancheng; ChenGang; CorreiaJosé A.F.O; QianGuian; ZhuShun-Peng
• Sommario/riassunto: The idea of preparing an Energies Special Issue on "Structural Prognostics and Health Management in Power & Energy Systems" is to compile information on the recent advances in structural prognostics and health management (SPHM). Continued improvements on SPHM have been made possible through advanced signature analysis, performance degradation assessment, as well as accurate modeling of failure mechanisms by introducing advanced mathematical approaches/tools. Through combining deterministic and probabilistic modeling techniques, research on SPHM can provide assurance for new structures at a design stage and ensure construction integrity at a fabrication phase. Specifically, power and energy system failures occur under multiple sources of uncertainty/variability resulting from load variations in usage, material properties, geometry variations within tolerances, and other uncontrolled variations. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on SPHM are desired and expected, which attempt to prevent overdesign and unnecessary inspection and provide tools to enable a balance between safety and economy to be achieved. This Special Issue has attracted submissions from China, USA, Portugal, and Italy. A total of 26 submissions were received and 11 articles finally published.
• Titolo autorizzato: Structural Prognostics and Health Management in Power & Energy Systems
• ISBN: 3-03921-767-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910372782603321
• Lo trovi qui: Univ. Federico II