Structural Prognostics and Health Management in Power & Energy Systems

• Autore: Wang Dong
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (218 p.)
• Soggetto non controllato: empirical mode decomposition; underground powerhouse; sensitivity analysis; DNN; fault detection; neural networks; structural health monitoring; analysis mode decomposition; dynamic analysis of the structure; residual useful life; renewable energy; remaining useful life; retrofitting activities; wind turbine blade; optimized deep belief networks; strain prediction; offshore wind turbines; low frequency tail fluctuation; oil and gas platforms; supporting vector machine (SVM); wave–structure interaction (WSI); sifting stop criterion; probabilistic analyses of stochastic processes and frequency; mode mixing; non-probabilistic reliability index; data-driven; prognostics; turbine blisk; wind turbines; supervisory control and data acquisition system; fuzzy safety criterion; analysis-empirical mode decomposition; rotation of hydraulic generator; life cycle cost; health monitoring; reliability; wavelet decomposition; weighted regression; similarity-based approach; vibration transmission mechanism; wind and wave analysis; full-scale static test; deep learning; multioperation condition; extremum surface response method; lithium-ion battery; vibration test; lateral-river vibration; operational modal analysis; dynamic analysis; regeneration phenomenon; machine learning; prognostic and Health Management; offshore structures; NAR neural network; techno-economic assessments; stochastic subspace identification; vertical axis wind turbine; dynamic fuzzy reliability analysis
• 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