IoT‐based approach to condition monitoring of the wave power generation system | Zendy

Qian Peng | Zendy; Feng Bo | Zendy; Zhang Dahai | Zendy; Tian Xiange | Zendy; Si Yulin | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

IoT‐based approach to condition monitoring of the wave power generation system

Author(s) -

Qian Peng,

Feng Bo,

Zhang Dahai,

Tian Xiange,

Si Yulin

Publication year - 2019

Publication title -

iet renewable power generation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.005

H-Index - 76

eISSN - 1752-1424

pISSN - 1752-1416

DOI - 10.1049/iet-rpg.2018.5918

Subject(s) - condition monitoring , computer science , electric power system , electricity generation , power (physics) , electrical engineering , engineering , physics , quantum mechanics

Accurate and reliable fault detecting plays a key role in application of grid‐connected wave power generation systems. This study presents a novel IoT‐based approach to condition monitoring of the wave power generation system, which has faster operating rate and lower hardware requirement. The compressed sensing (CS) method is adopted to compress the data, which aims to reduce the data uploaded to cloud platform; and then, the extreme learning machine (ELM) algorithm is used to achieve the condition monitoring of wave power generation system in cloud platform. In order to validate the effectiveness of the proposed method, the IoT‐based wave power generation condition monitoring system test platform is established. The experiment results illustrate the high efficiency and reliability of proposed method. The proposed method has a potential of practical applications.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research