A Liquid-solid Triboelectric Sensor for Minor and Invisible Leakage Monitoring in Ship Pipelines (May 2023)

• Published in: IEEE sensors journal Vol. 24; no. 3; p. 1
• Main Authors: Wang, Xinyu, Jiao, Xiaodong, Liang, Pengyu, Fei, Zelin, Guo, Wenxuan, Yang, Jinshan, Guan, Tangzhen, Sun, Hao, Tao, Jin, Zeng, Xianyi, Tao, Xuyuan, Jiang, Xingjia, Xu, Peng, Xu, Minyi, Sun, Qinglin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Series: IEEE Sensors Journal
• Subjects: Artificial neural networks; Data analysis; Droplets; Electric contacts; Engineering Sciences; High temperature; Hydrophobicity; Invisible and minor liquid leakage; Leakage; Liquid-solid triboelectric sensor; Marine environment; Monitoring; Nanogenerators; Pipelines; Protective coatings; Real time; Self-powered; Sensor arrays; Sensors; Ship pipeline monitoring; Silicon dioxide; Wear resistance; liquid-solid triboelectric sensor; Invisible and minor liquid leakage; self-powered; ship pipeline monitoring
• DOI: 10.1109/JSEN.2023.3336971
• ISSN: 1530-437X

Ship pipelines are the most efficient and cost-effective devices for liquid transportation. However, pipeline leakage can pose a threat to ship operation, human safety, and marine environment, especially for minor or invisible leakage with insufficient monitoring. Herein, we propose a triboelectric liquid leakage sensor (TLLS) based on a liquid-solid triboelectric nanogenerator (TENG), aiming at detecting, locating, and identifying the invisible and minor leakage of the ship pipelines in real time. The proposed device mainly consists of a steel electrode and SiO 2 /PTFE coating. When the coating contacts and separates from the leakage droplets, it generates electric signals that reflect the information of the droplets, such as their angle, temperature, height, volume, and type. The coating also has self-cleaning, superhydrophobic and wear-resistant properties, making it suitable for environments with vibration, high temperature, and humidity. In addition, the coating exhibits the potential to integrate with the prevailing ship steel structures, thereby enabling the formation of extensive sensor arrays for detecting leakages. From the experimental data analysis, the TLLS can obtain accurate information of minor or invisible leakage droplets. Moreover, an intelligence identification system based on the TLLS arrays and a lightweight artificial neural network is successfully developed. To highlight the stability and scalability of the developed system, real-time liquid droplet detection and identification are performed, showing great potential for ship pipeline monitoring and provides an intelligent method for modern ship management.