Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Echo State Network for the Remaining Useful Life Prediction of a Turbofan Engine

Among the various data-driven approaches used for RUL prediction, Recurrent Neural Networks (RNNs) have certain prima facie advantages over other approaches because the connections between internal nodes form directed cycles, thus creating internal states which enables the network to encapsulate dynamic temporal behavior and also to properly handle the noise affecting the collected signals. How...

متن کامل

Dimensionality Reduction Using Neural Networks

A multi-layer neural network with multiple hidden layers was trained as an autoencoder using steepest descent, scaled conjugate gradient and alopex algorithms. These algorithms were used in different combinations with steepest descent and alopex used as pretraining algorithms followed by training using scaled conjugate gradient. All the algorithms were also used to train the autoencoders withou...

متن کامل

Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life

Prognostics technique aims to accurately estimate the Remaining Useful Life (RUL) of a subsystem or a component using sensor data, which has many real world applications. However, many of the existing algorithms are based on linear models, which cannot capture the complex relationship between the sensor data and RUL. Although Multilayer Perceptron (MLP) has been applied to predict RUL, it canno...

متن کامل

Remaining Useful Life Estimation in Prognosis: An Uncertainty Propagation Problem

The estimation of remaining useful life is significant in the context of prognostics and health monitoring, and the prediction of remaining useful life is essential for online operations and decision-making. However, it is challenging to accurately predict the remaining useful life in practical aerospace applications due to the presence of various uncertainties that affect prognostic calculatio...

متن کامل

Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks

We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assumptions about how machines degrade. Additionally, sensor data from machines is noisy and o‰en su‚ers from missing values in many practical seŠings. We propose Embed-RUL: a novel approach for RUL estimation from sensor d...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Sensors

سال: 2020

ISSN: 1424-8220

DOI: 10.3390/s20226626