Self-Powered Wind Sensor System for Detecting Wind Speed and Direction Based on a Triboelectric Nanogenerator

Abstract

The development of the Internet of Things has brought new challenges to the corresponding distributed sensor systems. Self-powered sensors that can perceive and respond to environmental stimuli without an external power supply are highly desirable. In this paper, a self-powered wind sensor system based on an anemometer triboelectric nanogenerator (a-TENG, free-standing mode) and a wind vane triboelectric nanogenerator (v-TENG, single-electrode mode) is proposed for simultaneously detecting wind speed and direction. A soft friction mode is adopted instead of a typical rigid friction for largely enhancing the output performance of the TENG. The design parameters including size, unit central angle, and applied materials are optimized to enhance sensitivity, resolution, and wide measurement scale. The optimized a-TENG could deliver an open-circuit voltage of 88 V and short-circuit current of 6.3 μA, corresponding to a maximum power output of 0.47 mW (wind speed of 6.0 m/s), which is capable of driving electronics for data transmission and storage. The current peak value of the a-TENG signal is used for analyzing wind speed for less energy consumption. Moreover, the output characteristics of a v-TENG are further explored, with six actual operation situations, and the v-TENG delivers fast response to the incoming wind and accurately outputs the wind direction data. As a wind sensor system, wind speed ranging from 2.7 to 8.0 m/s can be well detected (consistent with a commercial sensor) and eight regular directions can be monitored. Therefore, the fabricated wind sensor system has great potential in wireless environmental monitoring applications.

Flexible and Stretchable Self‐Powered Multi‐Sensors Based on the N‐Type Thermoelectric Response of Polyurethane/Nax(Ni‐ett)n Composites

“…In cases like continuous monitoring, off-the-grid, and maintenance-free applications, self-powered sensors would be extremely desirable.Toward this aim, several energy harvesting strategies have been explored, based on triboelectricity, [4] piezoelectricity, [5] pyroelectricity, [6] and others. Examples of such devices include health monitoring devices, [1] soft robotics, [2] and functional artificial skin.…”

Low Detection Limit and High Sensitivity Wind Speed Sensor Based on Triboelectrification‐Induced Electroluminescence

“…These TENG-based sensors have been considered as one of the most effective mechanical energy conversion technologies as they enable the generation of high open-circuit voltage at a low frequency. Based on an anemometer TENG and a wind vane TENG, J. Y. Wang et al [16] presented a wind sensor with a sensing range from 2.7 to 8.0 m s −1 , which generates an output short-circuit current of 6.3 µA at wind speed of 6 m s −1 . [14] Y. Yang et al [15] reported a TENG-based wind speed sensing system, which displays a sensitivity of 0.09 µA/(m/s) and a detection limit 6 m s −1 by utilizing the wind-induced vibration.…”

Triboelectric Nanogenerator Based Smart Electronics via Machine Learning

“…The high sensitivity of TENG toward tiny vibration, the cost-effective fabrication process, and the flexible device structure provide much possibilities for the smart and interesting applications, such as humidity sensor, [10] pressure sensor, [11] active acoustic sensor, [12] ultraviolet detector, [13] Keystroke dynamics identification, [14] handheld printer, [15] and so on.Machine learning (ML) [16,17] is usually referred to statistical models and algorithms used by computer systems to conduct a specific task without too much complex instructions. The high sensitivity of TENG toward tiny vibration, the cost-effective fabrication process, and the flexible device structure provide much possibilities for the smart and interesting applications, such as humidity sensor, [10] pressure sensor, [11] active acoustic sensor, [12] ultraviolet detector, [13] Keystroke dynamics identification, [14] handheld printer, [15] and so on.…”