A Stochastic Spatio-Temporal Model of the Flow-Front Dynamics in a Vacuum Assisted Resin Transfer Moulding Process

被引：3

作者：

Nauheimer, Michael ^{[1
]}

Relan, Rishi ^{[2
]}

Thygesen, Uffe Hogsbro ^{[2
]}

Madsen, Henrik ^{[2
]}

Olesen, Bendt ^{[1
]}

Kirkeby, Klaus ^{[1
]}

机构：

[1] Siemens Gamesa Renewable Energy, Vejle, Denmark

[2] Tech Univ Denmark, DTU Compute, Aarhus, Denmark

来源：

IFAC PAPERSONLINE | 2018年 / 51卷 / 15期

关键词：

Wind turbines; Partial differential equations; Stochastic differential equations; Maximum Likelihood; Extended Kalman filter; Grey-box models; SIMULATION; SENSORS;

D O I：

10.1016/j.ifacol.2018.09.175

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With more emphasis on the use of green energy, the size of the turbines and blades in the wind turbines is continuously increasing. With increasing blade size, the casting process becomes more complicated and the risk of faults increases. Production of such blades, made of fibre reinforced polymer composites, without the possibility of visual inspection of the infusion process calls for a sensor system (possibly virtual) for monitoring the process. Therefore, in this paper, we propose a stochastic spatio-temporal modelling approach to model the flow-front dynamics inside the vacuum assisted resin transfer moulding process, knowledge of which is essential for determining the current state of the infusion process. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：383 / 388

页数：6

共 15 条

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