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BLTTNet: feature fusion based on BiLSTM-Transfomer-TCN for prediction of remaining useful life of aircraft engines. [PDF]

Sci Rep
Yang Y, Su X, Wang C, Liu H, Fu K, Xie T, Zhang Z.   +6 more
europepmc   +1 more source

Deep Learning Framework for Remaining Useful Life (RUL) Estimation in Turbofan Engines: A Bi-LSTM and Attention Mechanism Approach for Industrial Asset Integrity

Jean Firmino Cardoso, José Miguel Reichert, Antonio Celso Dantas Antonino   +2 more
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Multiclass classification for predicting Remaining Useful Life (RUL) of the turbofan engine

2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2021
For complex equipment and systems or their subsystems maintaining good health is very important. Several approaches were tried by the researchers applied by the industry professionals to predict the health of equipment, to take corrective measures. In this context, data analysis and machine learning are the latest tools that use historical data of ...
Piyush Soni, Mohd Anas Khan, Mohammad Zubair, Suresh Kumar Garg   +3 more
openaire   +1 more source

PROGNOS: an automatic remaining useful life (RUL) prediction model for military systems using machine learning

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 2022
In modern industrial settings, the quality of maintenance efforts directly influence equipment’s operational uptime and efficiency. Condition monitoring is a common process employed for predicting the health of a technical asset, whereby a predictive maintenance strategy can be adopted to minimize machine downtime and potential losses.
Sürücü O, Wilkinson C, Yeprem U, Hilal W, Gadsden SA, Yawney J, Alsadi N, Giuliano A   +7 more
openaire   +2 more sources

Remaining useful life (RUL) based maintenance decision making for deteriorating systems

IFAC Proceedings Volumes, 2012
This paper deals with a remaining useful life (RUL) based maintenance policy for single unit deteriorating systems whose condition are periodically monitored. Thank to the RUL information, which is estimated from the available monitoring information, various decisions related to inspections, logistic support, maintenance opportunities and maintenance ...
Do Van, Phuc, Levrat, Eric, Voisin, Alexandre, Iung, Benoît   +3 more
openaire   +2 more sources

Online prognostics of aircraft turbine engine component's remaining useful life (RUL)

IEEE SOUTHEASTCON 2014, 2014
Prognostics refers to the estimation of remaining useful life (RUL) of components of a system after a fault has been identified. Online prognostics indicates the estimation of RUL every time a new health data is provided to the user. In this paper, an artificial neural network (ANN) based approach is proposed for designing a prognostic system for ...
Md Monzurul Alam, M. Bodruzzaman, M. Saleh Zein-Sabatto   +2 more
openaire   +1 more source

Time-frequency complexity based remaining useful life (RUL) estimation for bearing faults

2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), 2013
Reliable operation of electrical machines depends on the timely detection and diagnosis of faults as well as on prognosis, i.e. estimating the remaining useful life (RUL) of the components. Bearings are the most common components in rotary machines and usually constitute a large portion of the failure cases in these machines.
Rodney K. Singleton, Elias G. Strangas, Selin Aviyente   +2 more
openaire   +1 more source

Estimation of remaining useful life (RUL) for pneumatic actuator without apriori RUL history: A hybrid prognostic approach

ISA Transactions
Predicting the Remaining Useful Life (RUL) of an industrial pneumatic actuator is crucial for enhancing maintenance strategies, reducing downtime and optimizing resource allocation. However, estimation becomes challenging when no historical RUL data is available for modeling.
Priyadarshini, Mahalingam, D, Kalpana, T, Thyagarajan   +2 more
openaire   +2 more sources

Remaining Useful Life (RUL) Prediction of Rolling Element Bearing Using Random Forest and Gradient Boosting Technique

Volume 13: Design, Reliability, Safety, and Risk, 2018
Rolling element bearings are very important and highly utilized in many industries. Their catastrophic failure due to fluctuating working conditions leads to unscheduled breakdown and increases accidental economical losses. Thus these issues have triggered a need for reliable and automatic prognostics methodology which will prevent a potentially ...
Sangram Patil, Aum Patil, Vishwadeep Handikherkar, Sumit Desai, Vikas M. Phalle, Faruk S. Kazi   +5 more
openaire   +1 more source