Сравнение на методи

	Прогностика и прогнозиране на оставащия полезен живот (RUL)	Актуализиране и калибриране на модел по метода на крайните елементи
Област	Инженерство на надеждността	Инженерство на надеждността
Семейство	Process / pipeline	Process / pipeline
Година на възникване	2000s	2001
Създател	George Vachtsevanos and others	John Mottershead and Michael Friswell
Тип	Predictive analytics methodology	System identification methodology
Основополагащ източник	Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. Wiley.	Mottershead, J. E., Link, M., & Friswell, M. I. (2011). The sensitivity method in finite element model updating: A tutorial. Mechanical Systems and Signal Processing, 25(7), 2275-2296.
Други названия	RUL, Remaining useful life, PHM, Prognostics and Health Management	Model updating, Model calibration, FEM updating
Свързани	4	4
Резюме	Prognostics and Health Management (PHM) is a methodology for predicting the remaining useful life (RUL) of equipment by monitoring its condition and extrapolating degradation trends. Unlike reactive maintenance (wait for failure) or preventive maintenance (fixed schedules), prognostics enable predictive maintenance: act only when failure is imminent. Formalized in the 2000s by researchers including George Vachtsevanos, RUL prediction integrates sensor data, degradation models, and uncertainty quantification to inform maintenance planning and reduce downtime.	Finite Element Model (FEM) Updating is the process of refining a numerical structural model to match measured behavior (modal properties, vibrations, static displacements) from the physical structure. By comparing computational predictions to experimental data and systematically adjusting uncertain model parameters (material properties, boundary conditions, joint stiffness), engineers create more accurate models for design decisions, damage detection, and life prediction. Formalized by Mottershead and Friswell, FEM updating bridges the gap between idealized computer models and real-world structures.