Design and Optimization of a Dual-Channel Differential Triboelectric Sensor for Underwater Low-Frequency Acoustic Detection
This work presents a novel marine acoustic sensor based on a differential dual-channel triboelectric nanogenerator (TENG) design for underwater low-frequency sound wave detection. By constructing a magnetically levitated vibration pickup system and optimizing the suspension height of the magnetic vibration system, the sensor achieves a resonant frequency of 35 Hz at a compact size of 18 mm in length, exhibiting high sensitivity to low-frequency acoustic waves and potential for deep-water applications. The differential sensing mechanism of the dual-channel TENG not only doubles the output voltage sensitivity of the triboelectric sensor but also significantly enhances its common-mode noise rejection capability. Compared to single-channel TENG sensors, the dual-channel differential TENG vector sensor (DTVS) demonstrates a markedly improved signal-to-noise ratio (SNR). The fabricated DTVS operates within a frequency range of 20–100 Hz, achieving a maximum sensitivity of 16.7 V/g in air. Underwater, its equivalent sound pressure sensitivity reaches up to −178.8 dB, with sensitivity fluctuations below 10 dB across the 20–100 Hz frequency band. Compared to traditional 8105 piezoelectric hydrophones, the DTVS exhibits superior low-frequency sensitivity and a more compact size. Additionally, it outperforms fiber-optic hydrophones and MEMS cilium hydrophones in terms of system simplicity, self-powered operation, and cost-effectiveness. The DTVS demonstrated a working depth of up to 200 meters underwater, with horizontal and vertical directivity resolutions reaching 30 dB, highlighting its promising potential as an underwater acoustic vector sensor.
Authors
- Zhenjun Liu (ORCID: https://orcid.org/0000-0002-5183-1619)
- Yiping Guo (ORCID: https://orcid.org/0000-0003-0251-450X)
- Chunling Shan (ORCID: https://orcid.org/0000-0002-5009-8726)
- Qichao Li (ORCID: https://orcid.org/0000-0002-4643-3069)
- Fu Chang
- Yuan Li (ORCID: https://orcid.org/0000-0002-0133-7516)
- Ge Song (ORCID: https://orcid.org/0000-0003-2782-2023)
- Xiongchao Ma
Institutions
- Shanghai Jiao Tong University (CN)
- Shanghai Power Equipment Research Institute (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jsen.2025.3581414
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shanghai Jiao Tong University