Graphene-Modified Fiber-Coating Tribovoltaic Sensor

Self-powered wear-state sensing

Monitors multidimensional motion states with high accuracy while maintaining bearing tribological performance, and when combined with deep learning, achieves 98.4% wear diagnosis accuracy.

Hongjie, Zhang · Gong, Likun · Zhang, Zhi · Zhang, Xiantao · Gao, Shuai · Wang, Song · Zhang, Chi · Han, Qingkai · Yan, Shaoze

Nano Energy 2026

Specifications

Diagnosis accuracy

98.4 %

Linear correlation coefficient

0.9986 R²

Advantages

Self-powered

Direct current output is generated at the friction interface without an external power source.

Non-intrusive

Monitoring does not compromise the bearing's tribological performance.

Multi-parameter

Rotational speed, load, and orientation can be simultaneously monitored.

Industrial validation

High linearity between signal frequency and actual rotational speed was validated on an industrial hydraulic reciprocating machine.

Applications

• Industrial IoT monitoring：Provides maintenance-free self-powered sensors for IIoT nodes.
• High-end equipment bearings：Enables online condition monitoring of bearings in high-end equipment.
• Self-powered sensing：Uses triboelectricity for in-situ powered sensing.