Results 111 to 120 of about 11,244 (210)

Fault Diagnosis and Prediction of Remaining Useful Life (RUL) of Rolling Element Bearing : A review state of art

Tribologia - Finnish Journal of Tribology
Fault diagnosis of rolling element bearings is a critical aspect of machine maintenance and reliability. Bearings are extensively used in various industrial applications, and their failure can lead to costly downtime and equipment damage. Rotating machinery under continuous overload conditions can indeed significantly degrade bearing life and lead to ...
Mogal, Shyam, R. V. Bhandare, V. M. Phalle, P. B. Kushare   +3 more
openaire   +2 more sources

Improving data-driven prognostics by assessing predictability of features.

, 2011
International audienceWithin condition based maintenance (CBM), the whole aspect of prognostics is composed of various tasks from multidimensional data to remaining useful life (RUL) of the equipment.
Gouriveau, Rafael, Javed, Kamran, Zemouri, Ryad, Zerhouni, Noureddine   +3 more
core   +1 more source

Prognostics with autoregressive moving average for railway turnouts [PDF]

, 2010
Turnout systems are one of the most critical systems on railway infrastructure. Diagnostics and prognostics on turnout system have ability to increase the reliability & availability and reduce the downtime of the railway infrastructure.
Camci, Faith, Eker, Ömer Faruk, Guclu, Adem, Jennions, Ian K., Yilboga, Halis   +4 more
core  

Remaining Useful Life Prediction Using Attention-LSTM Neural Network of Aircraft Engines

International Journal of Prognostics and Health Management
Accurate prediction of the Remaining Useful Life (RUL) is essential for the effective implementation of Prognostics and Health Management (PHM) in aerospace, particularly in enhancing aero-engine reliability and forecasting potential failures to reduce ...
Marouane Dida, Abdelhakim Cheriet, Mourad Belhadj   +2 more
doaj   +1 more source

A NEW PREDICTION METHOD FOR RUL PREDICTION OF CRUSHER ROLL IN NON STATIONARY PARTIALLY OBSERVED STATE

Jixie qiangdu, 2018
Accurate prediction of the remaining useful life（RUL） of the roller with double toothed roll crusher is an important basis for maintenance personnel to make scientific maintenance decision.
WU JianJun, LIU HaiPing, YE Xiang
doaj  

Integrating Machine Learning-Based Remaining Useful Life Predictions with Cost-Optimal Block Replacement for Industrial Maintenance

International Journal of Prognostics and Health Management
This study presents a preventive maintenance methodology to predict the remaining useful life (RUL) of mechanical systems and determine cost-effective replacement schedules.
Young-Suk Choo, Seung-Jun Shin
doaj   +1 more source

Turbofan Engine Remaining Useful Life (RUL) Prediction Based on Bi-Directional Long Short-Term Memory (BLSTM)

CoRR
The aviation industry is rapidly evolving, driven by advancements in technology. Turbofan engines used in commercial aerospace are very complex systems. The majority of turbofan engine components are susceptible to degradation over the life of their operation. Turbofan engine degradation has an impact to engine performance, operability, and reliability.
openaire   +2 more sources

Innovative Transformer-Driven Remaining Useful Life (RUL) Prediction Enhanced by Adaptive Multi-Scale Feature Engineering

Abstract Mechanical equipment often undergoes remaining life prediction (RUL) to ensure reliable, efficient, and optimal performance. A vast amount of industrial measurement data can significantly enhance the effectiveness of data-driven methods for RUL prediction.
Lydia Hsiao-Mei Lin, Fang-Kai Ting, Shu-Han Liao, Simon Hung-Yi Lu, Richard Tzong-Han Tsai   +4 more
openaire   +1 more source

An Algorithm to Detect and Predict the Remaining Useful Life (RUL), and an Exploratory Data Analysis (EDA) of the Traction Motor Performance

This study investigates and formulates a structured framework to guide deci-sion-making in the remanufacturing of spent electric vehicle (EV) traction motors. With a projected increase in the number of motors reaching end-of-life, the study tack-les key challenges by introducing a data-driven, integrated remanufacturing approach. A predictive algorithm
Edmund Antwi, Godwin Kafui Ayetor, Richard Opoku, Francis K. Forson   +3 more
openaire   +1 more source

A deep learning framework for remaining useful life prediction of turbofan engines with partial sensor failure. [PDF]

PLoS One
Tang D.
europepmc   +1 more source