Results 41 to 50 of about 419,717 (299)
Remaining useful life prediction for equipment based on RF-BiLSTM
AIP Advances, 2022 The prediction technology of remaining useful life has received a lot attention to ensure the reliability and stability of complex mechanical equipment. Due to the large-scale, non-linear, and high-dimensional characteristics of monitoring data, machine ...
Zhiqiang Wu +8 more
doaj +1 more source
A Data-Driven-Based Framework for Battery Remaining Useful Life Prediction
IEEE Access, 2023 Electric vehicles are expected to dominate the vehicle fleet in the near future due to their zero emissions of pollutants, reduced fossil fuel reserves, comfort, and lightness.
Amal Ezzouhri +3 more
doaj +1 more source
Remaining useful life prediction of rotating equipment using covariate-based hazard models : Industry applications [PDF]
, 2017 The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime
Yarlagadda, Prasad K. +5 more
core +1 more source
Predicting Remaining Useful Life with Similarity-Based Priors [PDF]
, 2020 Prognostics is the area of research that is concerned with predicting the remaining useful life of machines and machine parts. The remaining useful life is the time during which a machine or part can be used, before it must be replaced or repaired.
Wouter Duivesteijn +7 more
core +2 more sources
A Novel Deep Learning Approach for Machinery Prognostics Based on Time Windows
Applied Sciences, 2019 Remaining useful life (RUL) prediction is a challenging research task in prognostics and receives extensive attention from academia to industry. This paper proposes a novel deep convolutional neural network (CNN) for RUL prediction.
Hanbo Yang +4 more
doaj +1 more source
A remaining useful life prediction method based on PSR-former
Scientific Reports, 2022 The non-linear and non-stationary vibration data generated by rotating machines can be used to analyze various fault conditions for predicting the remaining useful life(RUL).
Huang Zhang +6 more
doaj +1 more source
Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation
Mathematics, 2022 All current deep learning-based prediction methods for remaining useful life (RUL) assume that training and testing data have similar distributions, but the existence of various operating conditions, failure modes, and noise lead to insufficient data ...
Yi Lyu +3 more
doaj +1 more source
Aero-Engine Remaining Useful Life Prediction Based on Bi-Discrepancy Network
Sensors, 2023 Most unsupervised domain adaptation (UDA) methods align feature distributions across different domains through adversarial learning. However, many of them require introducing an auxiliary domain alignment model, which incurs additional computational ...
Nachuan Liu +3 more
doaj +1 more source
Remaining Useful Life Estimation Using Functional Data Analysis [PDF]
2019 IEEE International Conference on Prognostics and Health Management (ICPHM), 2019 Accepted by IEEE International Conference on Prognostics and Health Management ...
Qiyao Wang +4 more
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction This study investigated the safety and efficacy of single‐needle Rheocarna therapy for chronic limb‐threatening ischemia (CLTI) with wounds. Methods Six patients with CLTI involving ulcers unresponsive to revascularization underwent single‐needle Rheocarna treatment.
Yasutaka Yamauchi +9 more
wiley +1 more source