Results 81 to 90 of about 10,974,174 (198)

Similarity-based Brownian Motion Approach for Remaining Useful Life Prediction

, 2021
International audienceThis paper proposes a data-driven framework for Remaining Useful Life (RUL) prediction of an operating equipment unit in the case of noisy and limited data. It consists of introducing the Brownian Motion model (BM) in the similarity
Pinaton, Jacques, Guillaume Graton, El Jamal, Dima, Dima El Jamal, Graton, Guillaume, Ouladsine, Mustapha, Bouchra Ananou, Jacques Pinaton, Ananou, Bouchra, Mustapha Ouladsine   +9 more
core   +1 more source

LiBrain: LLM‐powered Li‐ion battery diagnostics with time‐series‐aware retrieval‐augmented framework for E‐bikes

AI Magazine, Volume 47, Issue 3, Fall 2026.
Abstract The rapid proliferation of smart‐city ecosystems has significantly amplified the demand for Li‐ion batteries, which now serve as the primary energy source for sustainable transportation systems such as e‐bikes. Ensuring battery safety and optimal performance is crucial, yet challenging due to complex intrinsic dynamics and extrinsic operating ...
Zhao Li, Zixin Lin, Donghui Ding, Haitao Xu   +3 more
wiley   +1 more source

An Improved PF Remaining Useful Life Prediction Method Based on Quantum Genetics and LSTM

IEEE Access, 2019
Remaining useful life (RUL) is the premise and basis of the equipment health management plan. As accurate as possible life prediction is of great significance to reliability and economy of equipment maintenance.
Yang Ge, Lining Sun, Jiaxin Ma
doaj   +1 more source

Remaining useful life prediction of rotating machinery using hierarchical deep neural network

, 2017
This paper presents a novel approach for remaining useful life (RUL) prediction of rotating machinery using hierarchical deep neural networks (DNN). The different health stages are classified by a DNN-based health stage classifier trained by segmented ...
Liu, Lizhi, Xu, Lin, Gao, Shujun, Xia, Min, De Silva, Clarence W., Li, Teng   +5 more
core   +3 more sources

A New Strategy: Remaining Useful Life Prediction of Wind Power Bearings Based on Deep Learning under Data Missing Conditions

Mathematics
With its formidable nonlinear mapping capabilities, deep learning has been widely applied in bearing remaining useful life (RUL) prediction. Given that equipment in actual work is subject to numerous disturbances, the collected data tends to exhibit ...
Xuejun Li, Xu Lei, Lingli Jiang, Tongguang Yang, Zhenyu Ge   +4 more
doaj   +1 more source

Sequential Network with Residual Neural Network for Rotatory Machine Remaining Useful Life Prediction Using Deep Transfer Learning

Shock and Vibration, 2020
Deep learning has a strong feature learning ability, which has proved its effectiveness in fault prediction and remaining useful life prediction of rotatory machine.
Hao Zhang, Qiang Zhang, Siyu Shao, Tianlin Niu, Xinyu Yang, Haibin Ding   +5 more
doaj   +1 more source

Remaining Useful Life Prediction of Rolling Bearings Based on Recurrent Neural Network

, 2019
In order to acquire the degradation state of rolling bearings and achieve predictive maintenance, this paper proposed a novel Remaining Useful Life (RUL) prediction of rolling bearings based on Long Short Term Memory (LSTM) neural net-work. The method is
Jing Li, Qiang Cheng, Wei Ren, Yimeng Zhai, Aidong Deng   +4 more
core   +1 more source

Remaining Useful Life Prediction of Fracturing Truck Valve Bodies Based on the CB2-RUL Algorithm

Computation
The triplex reciprocating drilling pump is a critical piece of equipment in drilling platforms, and the operational condition of its core component—the valve body—directly affects the pump’s performance and the stability of the entire system. Therefore, accurate prediction of the valve body’s Remaining Useful Life (RUL) is of great significance for ...
Xinyue Chen, Jishun Ren, Yang Wang, Jiquan He, Xuyou Guo, Gantailai Ye   +5 more
openaire   +2 more sources

Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning

Complexity, 2018
Because they are key components of aircraft, improving the safety, reliability and economy of engines is crucial. To ensure flight safety and reduce the cost of maintenance during aircraft engine operation, a prognostics and health management system that
Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu
doaj   +1 more source

FDBRP: A Data–Model Co-Optimization Framework Towards Higher-Accuracy Bearing RUL Prediction

Sensors
This paper proposes Feature fusion and Dilated causal convolution model for Bearing Remaining useful life Prediction (FDBRP), an integrated framework for accurate Remaining Useful Life (RUL) prediction of rolling bearings that combines three key ...
Muyu Lin, Qing Ye, Shiyue Na, Dongmei Qin, Xiaoyu Gao, Qiang Liu   +5 more
doaj   +1 more source