Degradation Prediction Model Based on a Neural Network with Dynamic Windows
Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully re...
Main Authors: | Xinghui Zhang, Lei Xiao, Jianshe Kang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2015-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/15/3/6996 |
Similar Items
-
Prediction for the Remaining Useful Life of Lithium–Ion Battery Based on RVM-GM with Dynamic Size of Moving Window
by: Jinrui Nan, et al.
Published: (2022-01-01) -
The Remaining Useful Life Prediction Method of a Hydraulic Pump under Unknown Degradation Model with Limited Data
by: Fenghe Wu, et al.
Published: (2023-06-01) -
Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods
by: Joaquín de la Vega, et al.
Published: (2023-12-01) -
Remaining Useful Life Prediction for Two-Phase Nonlinear Degrading Systems with Three-Source Variability
by: Xuemiao Cui, et al.
Published: (2023-12-01) -
A Multi-Featured Factor Analysis and Dynamic Window Rectification Method for Remaining Useful Life Prognosis of Rolling Bearings
by: Cheng Peng, et al.
Published: (2023-11-01)