A ribbon-cage-based triboelectric bearing (RTB) is proposed and applied to the fault diagnosis of rotating machinery. Teflon insulating coatings are sprayed on the surface of the ribbon cage, and interdigital electrodes are pasted on the inner side of the dust cover to form a triboelectric nanogenerator with a free-standing mode. Owing to the direct use of the existing structure of rolling bearings (the ribbon cage and dust cover), only an insulating film and electrodes are added, and the designed RTB has an ultra-compact structure. Based on the fabricated RTB prototype, the variations in output voltage and current with load resistance are tested, and the effects of design parameters (including dielectric layer material and thickness, number of electrode section pairs, and spraying of Teflon coatings) on output characteristics are discussed. Through varying-speed tests, charging of load capacitors, and effective driving of micro-powered electronic devices, the self-sensing and self-powering capabilities of the proposed RTB are confirmed. A gear transmission test bench is constructed to perform fault diagnosis of rotating machinery based on the RTB output current. Combined with the time–frequency transformation and a deep learning algorithm, typical faults of rotating machinery (including localized faults in gears and bearings) are classified and recognized. The results show that the RTB output current can be used to diagnose faults in rotating machinery, and the classification accuracy can exceed 90%, which is only slightly lower than that obtained from the analysis using vibration signals. The proposed RTB has good application prospects for the fault diagnosis of rotating machinery.

Ultra-compact triboelectric bearing based on a ribbon cage with applications for fault diagnosis of rotating machinery

Gao, Shuai;Pennacchi, Paolo;
2022-01-01

Abstract

A ribbon-cage-based triboelectric bearing (RTB) is proposed and applied to the fault diagnosis of rotating machinery. Teflon insulating coatings are sprayed on the surface of the ribbon cage, and interdigital electrodes are pasted on the inner side of the dust cover to form a triboelectric nanogenerator with a free-standing mode. Owing to the direct use of the existing structure of rolling bearings (the ribbon cage and dust cover), only an insulating film and electrodes are added, and the designed RTB has an ultra-compact structure. Based on the fabricated RTB prototype, the variations in output voltage and current with load resistance are tested, and the effects of design parameters (including dielectric layer material and thickness, number of electrode section pairs, and spraying of Teflon coatings) on output characteristics are discussed. Through varying-speed tests, charging of load capacitors, and effective driving of micro-powered electronic devices, the self-sensing and self-powering capabilities of the proposed RTB are confirmed. A gear transmission test bench is constructed to perform fault diagnosis of rotating machinery based on the RTB output current. Combined with the time–frequency transformation and a deep learning algorithm, typical faults of rotating machinery (including localized faults in gears and bearings) are classified and recognized. The results show that the RTB output current can be used to diagnose faults in rotating machinery, and the classification accuracy can exceed 90%, which is only slightly lower than that obtained from the analysis using vibration signals. The proposed RTB has good application prospects for the fault diagnosis of rotating machinery.
2022
Triboelectric bearings; Nanogenerators; Ribbon cage; Fault diagnosis; Rotating machinery; Self-sensing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1215753
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