Recurrent Neural Networks for real-time distributed collaborative prognostics
Recurrent Neural Networks for real-time distributed collaborative prognostics
复制标题
用于实时分布式协作预测的循环神经网络
DOI：
10.1109/icphm.2018.8448622
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
A. Parlikad
中科院分区：
文献类型：
--
作者：
A. S. Palau;Kshitij Bakliwal;M. Dhada;Tim Pearce;A. Parlikad
我们展示了通过实施威布尔事件时间 - 循环神经网络 (WTTE-RNN) 算法实现实时分布式协作预测的第一步。在我们的系统中，资产根据与资产组中其他类似资产协作获得的特定于资产的模型实时确定其故障时间 (TTF)。所提出的方法建立在资产管理中相似性分析的新兴领域之上，并将其扩展到分布式协作预测。我们展示了如何通过资产和分布式预测之间的协作，获得有竞争力的无故障时间估计。11赞助商：Adrià Salvador 的工作得到了“Fundació la Caixa”提供的博士奖学金的赞助。这项研究还得到了 Sus-tainOwner（通过总价值和拥有成本实现工业资产的可持续设计和管理）的支持，该项目由欧盟框架计划 Horizon 2020、MSCA-RISE-2014：Marie Skodowska-Curie 研究和创新人员交流（Rise）赞助（拨款协议编号 645733 Sustain-owner H2020-MSCA-RISE-2014）。版权所有：978-1-5090-0382-2/16/$31.00 ©2018 IEEE
We present the first steps towards real-time distributed collaborative prognostics enabled by an implementation of the Weibull Time To Event - Recurrent Neural Network (WTTE-RNN) algorithm. In our system, assets determine their time to failure (TTF) in real-time according to an asset-specific model that is obtained in collaboration with other similar assets in the asset fleet. The presented approach builds on the emergent field of similarity analysis in asset management, and extends it to distributed collaborative prognostics. We show how through collaboration between assets and distributed prognostics, competitive time to failure estimates can be obtained.11Sponsors: Adrià Salvador work was sponsored by a Doctoral Scholarship provided by “Fundació la Caixa”. This research was also supported by Sus-tainOwner (Sustainable Design and Management of Industrial Assets through Total Value and Cost of Ownership) a project sponsored by the EU Framework Programme Horizon 2020, MSCA- RISE-2014: Marie Skodowska-Curie Research and Innovation Staff Exchange (Rise) (grant agreement number 645733 Sustain-owner H2020-MSCA-RISE-2014). Copyright: 978-1-5090-0382-2/16/$31.00 ©2018 IEEE
DOI：
10.1016/j.future.2018.02.011
发表时间：
2019-03
期刊：
Future Gener. Comput. Syst.
影响因子：
--
作者：
A. S. Palau;Zhenglin Liang;Daniel Lütgehetmann;A. Parlikad
通讯作者：
A. S. Palau;Zhenglin Liang;Daniel Lütgehetmann;A. Parlikad