A self-powered and self-monitoring ultra-low frequency wave energy harvester for smart ocean ranches
Yang Peng,
Hongjie Tang,
Hongye Pan,
Zutao Zhang,
Dabing Luo,
Minfeng Tang,
Weihua Kong,
Yingjie Li,
Genshuo Liu,
Yongli Hu
Affiliations
Yang Peng
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China; Yibin Research Institute, Southwest Jiaotong University, Yibin 644000, P.R. China
Hongjie Tang
School of Information Science and Technology, Chengdu 610031, P.R. China
Hongye Pan
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China
Zutao Zhang
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China; Chengdu Technological University, Chengdu 611730, China; Corresponding author
Dabing Luo
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China
Minfeng Tang
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China; Yibin Research Institute, Southwest Jiaotong University, Yibin 644000, P.R. China
Weihua Kong
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China; Yibin Research Institute, Southwest Jiaotong University, Yibin 644000, P.R. China
Yingjie Li
Tangshan Institute of Southwest Jiaotong University, Tangshan 063008, P.R. China
Genshuo Liu
Department of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Yongli Hu
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, P.R. China; Jinan Rail Transit Group Co., Ltd, Jinan, Shandong 250101, China
Summary: The ocean ranch environment contains ultra-low-frequency wave energy that can be utilized for powering low-power equipment. Therefore, this article proposes a smart ocean ranch self-powered and self-monitoring system (SOR-SSS) which consists of several key components: a mass pendulum ball (MPB), a commutation wheel system (CWS), an electromagnetic energy harvesting unit (EEHU), and four piezoelectric energy harvesting units (PEHU). Through six-degree-of-freedom vibration test bench experiments, the SOR-SSS achieved a maximum output power of 17.56 mW under a working condition of 0.4 Hz, which was sufficient to power 152 LED lights. Additionally, by training the experimental base data using the LSTM algorithm, two different tasks were trained with a maximum accuracy of 99.72% and 99.80%, respectively. These results indicate that the SOR-SSS holds significant potential for collecting and predicting ultra-low-frequency blue energy. It can provide an effective energy supply and monitoring solution for smart ocean ranch.
