Analytic and Nonlinear Prognostic for Vehicle Suspension Systems

Abstract

Predicting Remaining Useful Lifetime (RUL) of industrial systems becomes currently an important aim for industrialists knowing that the expensive failure can occur suddenly. As the classical strategies of maintenance are not efficient and practical because they neglect the evolving product state and environment, the recent prognostic approaches try to fill this gap. This approach shows to be important in ensuring high availability in minimum costs for industrial systems, like in aerospace, defense, petro-chemistry and automobiles. An analytic prognostic methodology based on existing damage laws in fracture mechanics, such as Paris’ and Miner’s laws, is recently developed for determining the system RUL. Damages have been assumed to be accumulated linearly, since we have considered the widely used linear Miner’s law. In this study, the nonlinear case in damage accumulation is explored to take into account the complex behavior of some materials subject to fatigue effects. It is useful especially when the nature of applied constraints and influent environment contribute to accentuate this nonlinearity. Our damage model is based on the accumulation of a damage measurement D(N) after each loading cycle N. In automobile industry, the prognostic assessment of the suspension component by this developed nonlinear approach shows its importance for the same earlier reasons.