remaining useful life (RUL)
A neural network filtering approach for similarity based remaining useful life estimation
... the remaining useful life of a test sample can be predicted by using the actual lifetime of similar examples so that the final prediction of RUL can be collaboratively estimated from multiple ...
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The Remaining Useful Life Estimation of Lithium-ion Battery Based on Improved Extreme Learning Machine Algorithm
... The common RUL prediction methods are divided into two categories: model-based prognostics methods and data-driven based methods [6]. Model-based prediction is a mathematical model with physical rules that can reflect ...
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NARX time series model for remaining useful life estimation of gas turbine engines
... Prognostics can be defined as the process of predicting the lifetime point at which a component or a system could not complete the proposed function planned during its design (Pecht, 2008). The amount of time from the ...
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Lithium-ion batteries Remaining Useful Life Prediction Method Considering Recovery Phenomenon
... In recent years, Prognostic and Health Management (PHM) has become a hot issue of research. As the core of PHM, RUL prediction has received extensive attention from industry and academia, and a large number of research ...
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Remaining Useful Life Assessment of Lithium-ion Battery based on HKA-ELM Algorithm
... Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is very important to battery management systems (BMS). Recently, Extreme Learning Machine (ELM) algorithm has been ...
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Feed Forward Backpropagation Neural Network Model to Predict Remaining Useful Life Estimation of Ion Implant Tool
... (useful) life (EOL) and/or the remaining useful life (RUL) of components, subsystems, or ...Usually, remaining useful life (RUL) estimation is a widely used form of ...
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Data Assimilation Algorithm for Remaining Useful Life Prediction of Aircraft Engine
... Remaining Useful Life (RUL) mainly refers to the remaining service life after a period of operation of the system, accurately predicting the remaining useful life ...
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Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques
... and remaining useful life of wind turbine gearboxes, enough examples of the exact same failure mode exist to allow for failure mode specific remaining useful life predictions, ...
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The Remaining Useful Life Estimation of Lithium-ion Batteries Based on the HKA -ML-ELM Algorithm
... the remaining useful life (RUL) of lithium-ion batteries is of great significance for battery management and ensuring the reliability of electronic ...
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Prediction of Remaining Useful Life for Lithium-Ionbattery with Multiple Health Indicators
... its remaining useful life ...of remaining charge-discharge cycles before the battery capacity deteriorates to a predetermined failure threshold ...
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Lithium-ion Battery Remaining Useful Life Prediction Based on Exponential Smoothing and Particle Filter
... Inspired by the limitations of the model-based methods mentioned above, this paper proposes a novel hybrid method composed of a particle filter (PF), exponential smoothing (ES) and an empirical capacity degradation model ...
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Prediction of the Remaining Useful Life of Aircraft Systems via Web Interface
... Abstract—In this work a web-based tool is presented for the simulation of a Prognostics and Health Management (PHM) system used for exploring and test- ing different machine learning experimental scenarios with the goal ...
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Remaining Useful Life Model and Assessment of Mechanical Products: A Brief Review and a Note on the State Space Model Method
... The remaining useful life (RUL) prediction of mechanical products has been widely studied for online system per- formance reliability, device remanufacturing, and product safety (safety awareness and ...
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A Bayesian Quantitative Nondestructive Evaluation (QNDE) Approach to Estimating Remaining Useful Life of Aging Pressure Vessels and Piping
... the remaining useful life of an aging structure by a Bayesian quantitative nondestructive evaluation (Q-NDE) approach, where the key emphasis is in first obtaining as much as possible the relevant ...
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An adaptive data filtering model for remaining useful life estimation
... Due to the incomplete understanding on the multi-dimensional failure mech- anisms and the collaboration between data sources, current prognostic methods lack the ability to deal effectively with complicated ...
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Data Driven Approach to Non-stationary EMA Fault Detection and Investigation Into Remaining Useful Life
... Narasimhan et al. [1] investigated twelve EMA fault conditions includ- ing nut jam, motor failure, spall, and many sensor faults using a hybrid architecture applied to the Flyable Electromechanical Actuator (FLEA) sys- ...
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Outlier Modeling in Gear Bearing Using Autoencoder for Remaining Useful Life Prediction
... A number of distinguished engineers and scholars have also conducted reviews of RUL prediction. Heng et al. [11] summarised conventional reliability models, condition-based prognostic models, and their hybrid models. Ye ...
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Sequential Monte Carlo Method Toward Online RUL Assessment with Applications
... of remaining useful life (RUL) of a system or device has been widely studied for performance reli‑ ability, production safety, system conditional maintenance, and decision in remanufacturing ...
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A Study on Remaining Useful Life Prediction for Prognostic Applications
... For other uses you need to obtain permission from the rights- holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work i[r] ...
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A New Health Assessment Prediction Approach: Multi-Scale Ensemble Extreme Learning Machine
... Remaining Useful Life (RUL) of complex systems based on conventional prediction paradigms such as physical modeling can be considered as very difficult task due to the need of the deep knowledge of ...
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