04871nam 2201057z- 450 991037278260332120231214133436.03-03921-767-4(CKB)4100000010163798(oapen)https://directory.doabooks.org/handle/20.500.12854/60148(EXLCZ)99410000001016379820202102d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierStructural Prognostics and Health Management in Power & Energy SystemsMDPI - Multidisciplinary Digital Publishing Institute20201 electronic resource (218 p.)3-03921-766-6 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.empirical mode decompositionunderground powerhousesensitivity analysisDNNfault detectionneural networksstructural health monitoringanalysis mode decompositiondynamic analysis of the structureresidual useful liferenewable energyremaining useful liferetrofitting activitieswind turbine bladeoptimized deep belief networksstrain predictionoffshore wind turbineslow frequency tail fluctuationoil and gas platformssupporting vector machine (SVM)wave–structure interaction (WSI)sifting stop criterionprobabilistic analyses of stochastic processes and frequencymode mixingnon-probabilistic reliability indexdata-drivenprognosticsturbine bliskwind turbinessupervisory control and data acquisition systemfuzzy safety criterionanalysis-empirical mode decompositionrotation of hydraulic generatorlife cycle costhealth monitoringreliabilitywavelet decompositionweighted regressionsimilarity-based approachvibration transmission mechanismwind and wave analysisfull-scale static testdeep learningmultioperation conditionextremum surface response methodlithium-ion batteryvibration testlateral-river vibrationoperational modal analysisdynamic analysisregeneration phenomenonmachine learningprognostic and Health Managementoffshore structuresNAR neural networktechno-economic assessmentsstochastic subspace identificationvertical axis wind turbinedynamic fuzzy reliability analysisWang Dongauth596182Zhang XianchengauthChen GangauthCorreia José A.F.OauthQian GuianauthZhu Shun-PengauthBOOK9910372782603321Structural Prognostics and Health Management in Power & Energy Systems3020962UNINA