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Journal ArticleDOI

Remaining useful life prediction based on a multi-sensor data fusion model

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TLDR
A RUL prediction method based on a multi-sensor data fusion model where the inherent degradation process of the system state is expressed using a state transition function following a Wiener process.
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This article is published in Reliability Engineering & System Safety.The article was published on 2021-04-01. It has received 61 citations till now. The article focuses on the topics: Sensor fusion & Prognostics.

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Citations
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Journal ArticleDOI

Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction

TL;DR: Wang et al. as discussed by the authors proposed a hierarchical attention graph convolutional network (HAGCN) to model the sensor network and the hierarchical graph representation layer is proposed for modeling spatial dependencies of sensors and bi-directional long shortterm memory network is used for modeling temporal dependencies of sensor measurements.
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Fault prediction of bearings based on LSTM and statistical process analysis

TL;DR: A novel model named LSS which combines the advantages of long short-term memory (LSTM) network with statistical process analysis to predict the fault of aero-engine bearings with multi-stage performance degradation with higher prediction accuracy is proposed.
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2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing

TL;DR: A multi-sensor and multi-scale model (2MNet) is proposed to bring a new perspective to accurate fault diagnosis of rolling bearing, showing superiority and applicability of the model by numerical simulation and rolling bearing data.
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Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture

TL;DR: In this article , a double attention-based data-driven framework for aircraft engine RUL prognostics was proposed, where the channel attention was utilized to apply greater weights to more significant features and a Transformer was used to focus attention on these features at critical time steps.
References
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Journal ArticleDOI

A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

TL;DR: Both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters are reviewed.
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Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting

TL;DR: Locally weighted regression as discussed by the authors is a way of estimating a regression surface through a multivariate smoothing procedure, fitting a function of the independent variables locally and in a moving fashion analogous to how a moving average is computed for a time series.
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Machinery health prognostics: A systematic review from data acquisition to RUL prediction

TL;DR: A review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction, which provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.
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The inverse gaussian distribution: theory, methodology, and applications

TL;DR: Inverse Gaussian distributions have been used for life testing and reliability as mentioned in this paper, and they have been applied in a variety of applications, such as life testing, reliability, and life assurance.
Journal ArticleDOI

A Model-Based Method for Remaining Useful Life Prediction of Machinery

TL;DR: A model-based method for predicting RUL of machinery is proposed and the effectiveness of the proposed method is identified, using vibration signals from accelerated degradation tests of rolling element bearings.
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