TY - JOUR
T1 - Study on Condition Monitoring of Pitch Bearings Based on Stress Measurement
AU - Wu, Zian
AU - Yang, Wenxian
AU - Song, Xiaoping
AU - Wei, Kexiang
N1 - Funding Information:
The work reported above was supported by the National Natural Science Foundation of China (52175089 and 12002125).
Publisher Copyright:
© 2024 by the authors.
PY - 2024/3/1
Y1 - 2024/3/1
N2 - Pitch bearings in wind turbines are crucial components that enable safe blade pitching, optimize electrical power output, and ensure turbine protection. Traditional vibration analysis-based methods used for high-speed bearings are not applicable to monitoring pitch bearings, due to its slow non-integer cycle rotation. To address this issue, a stress-based pitch bearing monitoring method is proposed in this paper. First, finite element analysis is conducted to establish the relationship between the maximum surface stress on the outer race of the pitch bearing and the presence of cracks. This relationship allows the identification of cracks on the outer race and an assessment of their severity based on the value of the maximum surface stress. Second, the outer race of the pitch bearing is divided into several segments, and a singularity detection technique is employed to locate the position of cracks on the outer race based on the stresses measured from the segments. To verify the proposed method, a wind turbine pitch bearing test rig was developed in a laboratory. Experimental results have shown that the proposed method can effectively and accurately identify and locate cracks on the outer race of the bearing, thereby demonstrating its great potential as a reliable approach for monitoring the condition of wind turbine pitch bearings.
AB - Pitch bearings in wind turbines are crucial components that enable safe blade pitching, optimize electrical power output, and ensure turbine protection. Traditional vibration analysis-based methods used for high-speed bearings are not applicable to monitoring pitch bearings, due to its slow non-integer cycle rotation. To address this issue, a stress-based pitch bearing monitoring method is proposed in this paper. First, finite element analysis is conducted to establish the relationship between the maximum surface stress on the outer race of the pitch bearing and the presence of cracks. This relationship allows the identification of cracks on the outer race and an assessment of their severity based on the value of the maximum surface stress. Second, the outer race of the pitch bearing is divided into several segments, and a singularity detection technique is employed to locate the position of cracks on the outer race based on the stresses measured from the segments. To verify the proposed method, a wind turbine pitch bearing test rig was developed in a laboratory. Experimental results have shown that the proposed method can effectively and accurately identify and locate cracks on the outer race of the bearing, thereby demonstrating its great potential as a reliable approach for monitoring the condition of wind turbine pitch bearings.
KW - condition monitoring
KW - pitch bearing
KW - singularity detection
KW - stress
KW - wind turbine
UR - http://www.scopus.com/inward/record.url?scp=85189029946&partnerID=8YFLogxK
U2 - 10.3390/machines12030154
DO - 10.3390/machines12030154
M3 - Article
AN - SCOPUS:85189029946
VL - 12
JO - Machines
JF - Machines
SN - 2075-1702
IS - 3
M1 - 154
ER -