Affiliation:
1. School of Mathematics and Statistics Beijing Institute of Technology Beijing China
2. Institute of Chemical Materials China Academy of Engineering Physics Mianyang China
Abstract
AbstractWax is a prevalent lubrication material extensively employed in various engineering applications. Understanding the degradation characteristics of the waxy lubrication layer under diverse stress variables and levels is crucial for ensuring system security and reliability. Due to the unclear mechanism governing the degradation of the waxy lubrication layer under different stress variables, existing degradation models are unsuitable for modeling waxy lubrication layer degradation data. To address this challenge, we propose a functional data‐driven method leveraging dense observations of waxy degradation. Through extensive simulations and a case study, we demonstrate the superior performance and effectiveness of the proposed approach.
Funder
Foundation of President of China Academy of Engineering Physics
National Natural Science Foundation of China