TY - JOUR
T1 - Symmetrical Triboelectric In Situ Self-Powered Sensing and Fault Diagnosis for Double-Row Tapered Roller Bearings in Wind Turbines
T2 - An Integrated and Real-Time Approach
AU - Wang, Song
AU - Zhang, Xiantao
AU - Ma, Tenghao
AU - Kong, Yun
AU - Gao, Shuai
AU - Han, Qinkai
N1 - Publisher Copyright:
© 2025 The Author(s). Advanced Science published by Wiley-VCH GmbH.
PY - 2025/5/22
Y1 - 2025/5/22
N2 - Double-row tapered roller bearings (DTRBs) are widely used in wind turbines because of their high load-bearing capacity and durability. However, wind turbines typically operate in harsh environments, subjecting bearings to complex working conditions, which significantly increases the difficulty of operational status monitoring. Traditional monitoring methods rely on external power sources and complex sensor networks, which make them susceptible to environmental interference, and complicated to maintain. This paper presents an innovative, integrated symmetrical single-electrode triboelectric double-row tapered roller bearing (SST-DTRB) by incorporating a triboelectric nanogenerator (TENG) with DTRB. This scheme converts the frictional energy generated during bearing operation into electrical output, producing signals that enable simultaneous sensing of both ends of DTRB. Experimental results demonstrate that this monitoring scheme exhibits high sensitivity, stability, and reliability, with excellent robustness in material selection and design gap, and is capable of long-term operation without external power sources. The effectiveness and self-sensing capability of SST-DTRB under variable speeds are validated using a wind turbine test bench. High-accuracy bearing fault diagnosis under multiple conditions is achieved based on time-frequency transformation and deep residual neural networks. The proposed SST-DTRB provides in situ self-powered sensing capability for wind turbines and offers new insights in the development of intelligent sensing systems.
AB - Double-row tapered roller bearings (DTRBs) are widely used in wind turbines because of their high load-bearing capacity and durability. However, wind turbines typically operate in harsh environments, subjecting bearings to complex working conditions, which significantly increases the difficulty of operational status monitoring. Traditional monitoring methods rely on external power sources and complex sensor networks, which make them susceptible to environmental interference, and complicated to maintain. This paper presents an innovative, integrated symmetrical single-electrode triboelectric double-row tapered roller bearing (SST-DTRB) by incorporating a triboelectric nanogenerator (TENG) with DTRB. This scheme converts the frictional energy generated during bearing operation into electrical output, producing signals that enable simultaneous sensing of both ends of DTRB. Experimental results demonstrate that this monitoring scheme exhibits high sensitivity, stability, and reliability, with excellent robustness in material selection and design gap, and is capable of long-term operation without external power sources. The effectiveness and self-sensing capability of SST-DTRB under variable speeds are validated using a wind turbine test bench. High-accuracy bearing fault diagnosis under multiple conditions is achieved based on time-frequency transformation and deep residual neural networks. The proposed SST-DTRB provides in situ self-powered sensing capability for wind turbines and offers new insights in the development of intelligent sensing systems.
KW - fault diagnosis
KW - in situ self-powered sensing
KW - triboelectric nanogenerator
KW - wind turbine
UR - https://www.scopus.com/pages/publications/105000862722
U2 - 10.1002/advs.202500981
DO - 10.1002/advs.202500981
M3 - Article
C2 - 40126398
AN - SCOPUS:105000862722
SN - 2198-3844
VL - 12
JO - Advanced Science
JF - Advanced Science
IS - 19
M1 - 2500981
ER -