Self-powered active vibration sensor by peak–valley data processing independent of the environment toward structural health monitoring

Abstract

Vibration sensors are in high demand in the field of structural health monitoring. Nevertheless, most of them are limited by their requirement of external power supplies. Moreover, self-powered active sensors supplied by triboelectric nanogenerators (TENGs) are susceptible to environment changes, in particular, ambient temperature and humidity, which seriously degrade the measurement accuracy and stability of the sensors. Hence, a self-powered active vibration sensor (SPAVS) based on TENGs for structural health monitoring is proposed. Due to the unique electrode design and novel signal processing strategy, the SPAVS can effectively overcome the working environmental dependence of the self-powered active sensor based on the signal amplitude. The results indicate that the SPAVS can sense vibration displacements, velocities and accelerations. In addition, by identifying the shape of the short-circuit current and employing signal processing algorithms, effective sensing of vibration types can be realised. Based on the features mentioned above, the proposed SPAVS has potential applications in monitoring the structural health in the area of the detection of vibration in the bridges, disaster prevention and mitigation of large buildings in the near future. They have advantages in wider temperature ranges and in cases of higher humidity due to them being inherently unaffected by the ambient environment.