Data-Driven Prognostics of Alternating Current Solenoid Valves

@article{Mazaev2020DataDrivenPO,
  title={Data-Driven Prognostics of Alternating Current Solenoid Valves},
  author={Tamir Mazaev and Agusmian Partogi Ompusunggu and Georges Tod and Guillaume Crevecoeur and Sofie Van Hoecke},
  journal={2020 Prognostics and Health Management Conference (PHM-Besançon)},
  year={2020},
  pages={109-115}
}
Solenoid valves are critical components in many process control systems, as their failure is often a root cause for plant shutdowns. Therefore, the ability to predict the remaining useful life (RUL) of solenoid valves is highly desirable. In this paper, a novel data-driven RUL prediction methodology for solenoid valves is proposed, by training deep neural networks on images constructed from raw current signatures. The performance is compared to shallow machine learning algorithms, trained on… 
Experimental and numerical validation of a proportional solenoid valve based on the data-driven model
TLDR
A dynamical model is very important for the design and control of a solenoid valve and its application in mechatronics, robotic systems and industrial occasions.

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