A wind vector detecting system based on triboelectric and photoelectric sensors for simultaneously monitoring wind speed and direction

The wind vector sensor is a significant category of Internet of Things (IoTs) based sensors due to its irreplaceable role in weather monitoring, traffic detection, and mine safety. However, searching new power supply approaches, apart from batteries, for this type of sensor is a critical issue hindering its widespread application because of the vast number of sensor nodes. Self-powered technology based on nanogenerator offers great promise for resolving the dilemma. Herein, we propose a novel wind vector sensor system for synchronously perceiving wind speed and direction based on the coupling of self-powered triboelectric sensor and photoelectric technology. For wind speed detection, an angle-shaped triboelectric sensor (ASTS) is well designed and systemically investigated. The ASTS after structure optimization exhibits a low start-up wind speed and considerable outputs. A wide wind speed sensing range is achieved from 2.9 m/s to 24.0 m/s, within which the current frequency of ASTS shows a good proportional relationship with wind speed. Furthermore, a wind direction sensor (WDS) based on photoelectric detection is carefully fabricated to integrate with the ASTS for wind vector monitoring. Specific algorithms and programs are developed through the LabVIEW platform to process the electric signals from the system and visually display the results on the screen. The practical application demonstrates that the proposed wind vector sensing system is capable of accurately identifying wind speed from eight directions. This work would pave the way to achieve the ultra-low power consumption for IoTs-based environmental sensors.

Automated summary

This paper proposes a novel wind vector sensor system that can synchronously perceive wind speed and direction based on self-powered technology and photoelectric technology, achieving accurate monitoring of wind direction and paving the way for ultra-low power consumption for IoTs-based environmental sensors.