Life Prediction

Life prediction research focuses on accurately estimating the remaining useful life (RUL) of various systems, from batteries and engines to electronic components and even human lifespans, aiming to optimize maintenance, improve safety, and enhance resource management. Current research heavily utilizes machine learning, employing diverse architectures like neural networks (including Bayesian and recurrent types), GraphNets, and transformers, often incorporating physics-informed models or leveraging techniques like domain adaptation and self-supervised learning to improve prediction accuracy and robustness under data scarcity or varying operating conditions. These advancements have significant implications across numerous industries, enabling predictive maintenance, improving product design, and facilitating more informed decision-making in diverse applications.

Papers

September 22, 2024

Sparse Low-Ranked Self-Attention Transformer for Remaining Useful Lifetime Prediction of Optical Fiber Amplifiers
Dominic Schneider, Lutz Rapp
Self Attention Optical Communication Life Prediction Remaining Useful

August 14, 2024

Battery GraphNets : Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation
Sakhinana Sagar Srinivas, Rajat Kumar Sarkar, Venkataramana Runkana
Graph Neural Network Lithium Ion Battery Ion Battery Relational Learning Life Prediction Battery Degradation Battery Datasets

July 9, 2024

Sampling and active learning methods for network reliability estimation using K-terminal spanning tree
Chen Ding, Pengfei Wei, Yan Shi, Jinxing Liu, Matteo Broggi, Michael Beer
Active Learning Open Sampling K Content Life Prediction Structure Function Network Reliability

May 28, 2024

Towards robust prediction of material properties for nuclear reactor design under scarce data -- a study in creep rupture property
Yu Chen, Edoardo Patelli, Zhen Yang, Adolphus Lye
Native Robustness Robust Learning Robust Prediction Material Property Scarce Data Life Prediction Nuclear Reactor Trustworthy Prediction

May 10, 2024

Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants
Ibai Ramirez, Joel Pino, David Pardo, Mikel Sanz, Luis del Rio, Alvaro Ortiz, Kateryna Morozovska, Jose I. Aizpurua
Transformer Megatron Decepticons Transformer Based Decision Transformer Life Prediction Hotspot Detection Power Transformer

November 13, 2023

Novel models for fatigue life prediction under wideband random loads based on machine learning
Hong Sun, Yuanying Qiu, Jing Li, Jin Bai, Ming Peng
Machine Learning Machine Learning Model Dynamic Loading Life Prediction Novel Model Fatigue Life Prediction

November 4, 2023

Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks
Longze Li, Jiang Chang, Aleksandar Vakanski, Yachun Wang, Tiankai Yao, Min Xian
Uncertainty Quantification Bayesian Neural Network Material Property Prediction Multivariate Regression Life Prediction Bayesian Physic Informed Neural Network

August 27, 2023

Improve in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging
Mingyuan Zhao, Yongzhi Zhang
Classification Performance Current State Life Prediction Battery Lifetime Mutation Rate

July 17, 2023

Predicting Battery Lifetime Under Varying Usage Conditions from Early Aging Data
Tingkai Li, Zihao Zhou, Adam Thelen, David Howey, Chao Hu
Greater Public Use Lithium Ion Battery Ion Battery Life Prediction Age Datasets Battery Degradation Battery Lifetime

March 15, 2023

Large-scale End-of-Life Prediction of Hard Disks in Distributed Datacenters
Rohan Mohapatra, Austin Coursey, Saptarshi Sengupta
Encoder Decoder Data Center Life Prediction Sequence Learning

February 3, 2023

Domain Adaptation via Alignment of Operation Profile for Remaining Useful Lifetime Prediction
Ismail Nejjar, Fabian Geissmann, Mengjie Zhao, Cees Taal, Olga Fink
Domain Adaptation Domain Shift Alignment Problem Prognostic Model Domain Shift Problem Life Prediction Remaining Useful Operational Technology

January 19, 2023

Estimating Remaining Lifespan from the Face
Amir Fekrazad
Human Face Life Prediction Biological Age

November 10, 2022

Bayesian hierarchical modelling for battery lifetime early prediction
Zihao Zhou, David A. Howey
Ion Battery Early Prediction Battery Health Life Prediction Battery Lifetime

July 4, 2022

Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools
Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad, Weng Khuen Ho, Tong Heng Lee
Deep Learning Model Industrial Machine Life Prediction Industrial Monitoring Remaining Useful Life Prediction Masked Unsupervised Self Training

April 13, 2022

Performance Assessment of different Machine Learning Algorithm for Life-Time Prediction of Solder Joints based on Synthetic Data
Stefan Muench, Darshankumar Bhat, Leonhard Heindel, Peter Hantschke, Mike Roellig, Markus Kaestner
Synthetic Data Long Short Term Memory Multi Layer Machine Learning Algorithm Performance Evaluation Life Prediction Finite Element Model Different Machine Learning

March 19, 2022

Life Prediction

Papers

Sparse Low-Ranked Self-Attention Transformer for Remaining Useful Lifetime Prediction of Optical Fiber Amplifiers

Battery GraphNets : Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation

Sampling and active learning methods for network reliability estimation using K-terminal spanning tree

Towards robust prediction of material properties for nuclear reactor design under scarce data -- a study in creep rupture property

Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants

Novel models for fatigue life prediction under wideband random loads based on machine learning

Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks

Improve in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging

Predicting Battery Lifetime Under Varying Usage Conditions from Early Aging Data

Large-scale End-of-Life Prediction of Hard Disks in Distributed Datacenters

Domain Adaptation via Alignment of Operation Profile for Remaining Useful Lifetime Prediction

Estimating Remaining Lifespan from the Face

Bayesian hierarchical modelling for battery lifetime early prediction

Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools

Performance Assessment of different Machine Learning Algorithm for Life-Time Prediction of Solder Joints based on Synthetic Data

Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers