Triboelectric nanogenerator embedded cylindrical roller bearing for rotational energy harvesting and self-powered fault diagnosis

• Published in: Sensors and actuators. A. Physical. Vol. 362; p. 114664
• Main Authors: Xin, Yida, Du, Taili, Liu, Ting, Sun, Peiting, Zhu, Meixian, Zheng, Lin, Du, Haiying, Zou, Yongjiu, Xu, Minyi
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2023
• Subjects: Fault diagnosis; Self-powered; Smart bearing; Triboelectric nanogenerator; Fault diagnosis; Triboelectric nanogenerator; Self-powered; Smart bearing
• ISSN: 0924-4247
• DOI: 10.1016/j.sna.2023.114664

Ensuring the normal operation of bearings is crucial for the safety of the equipment. In order to better monitor the condition of bearings, a smart triboelectric nanogenerator embedded cylindrical roller bearing (TCRB) is proposed. Its cylindrical rollers are made of polyetheretherketone (PEEK), and the outer ring consists of grid electrodes coated with nylon film. The present TCRB is demonstrated to achieve long-term stable operation. Experimentally, the TCRB can deliver a maximum output with an open-circuit voltage of 26.56 V and a short-circuit current of 2.45 µA at 600 rpm, and the generated electricity is sufficient to drive small sensors. Moreover, the output can also be processed to realize the self-powered monitoring of the rotational speed with an error of less than 2%. Lastly, four distinct classification methods are utilized to diagnose typical bearing faults using the triboelectric signal, and the diagnostic method with both high levels of accuracy and robustness is determined. This study demonstrates the excellent performance of the TCRB in self-powering, self-sensing and self-diagnosing, providing a viable solution for the development of smart bearings. [Display omitted] •A triboelectric nanogenerator embedded cylindrical roller smart bearing (TCRB) is proposed.•The TCRB is capable of supplying power to condition monitoring sensors.•Through processing of the output, the TCRB can realize real-time speed sensing function.•An in-depth research is conducted utilizing triboelectric signals for fault diagnosis.