Tooth backlash inspired comb-shaped single-electrode triboelectric nanogenerator for self-powered condition monitoring of gear transmission

Abstract

Gear transmissions are an integral part of most rotation machinery. Their abnormalities can affect the reliable operation of the equipment. Most sensors that monitor gear transmissions lack self-powered capability and have weak features due to the restricted mounting locations. In this study, the tooth backlash inspired triboelectric nanogenerator (TB-TENG) is proposed for self-powered condition monitoring of the gear transmissions. A series of comb-shaped copper foil electrodes is arranged on the non-load tooth sides to create a single-electrode TENG. Through the rational use of the tooth backlash space, the TB-TENG does not affect the tooth meshing or participate in the load transmission, ensuring both durability and structural compactness. The TB-TENG outputs are evaluated under various working conditions, structural optimizations, and different working environments based on the established TB-TENG test system. Consequently, the maximum output power density corresponding to the optimal resistance is obtained. Based on the output signal model, the effectiveness of the TB-TENG in self-powered condition monitoring is verified. Moreover, the denoising convolutional auto-encoder (DCAE) is trained based on the TB-TENG voltage signals, achieving a diagnostic accuracy of 98.4%, equivalent to accuracy based on vibration signals. The practical applicability of the proposed TB-TENG is demonstrated through deployment testing in an industrial parallel-gear transmission system. Specifically, TB-TENG can accurately monitor gear speed under variable speed conditions to assess operation stability and health status. Finally, the theoretical and experimental basis for the TB-TENG is provided with applications for self-powered condition monitoring.