Yangxia Xiang
Papers
1
Total Citations
29
H-Index
1
About
Dr. Yangxia Xiang is a leading researcher in industrial robotics and mechanical fault diagnosis, with a focus on the reliability of critical drivetrain components. Her work centers on developing advanced signal processing and deep learning methodologies for the early detection of failures in Harmonic Drives (HDs)—the precision gears essential to modern robotic arms. In her highly cited 2023 study, "Fault Diagnosis of Harmonic Drives Based on an SDP-ConvNeXt Joint Methodology," Dr. Xiang introduced a novel approach that fuses Symmetrized Dot Pattern (SDP) imaging with the ConvNeXt convolutional neural network architecture. This method enables the accurate classification of HD faults under real-world, noisy operating conditions, directly addressing the risk of robot paralysis and operational accidents caused by undetected drivetrain damage. With 29 citations for this single paper, her work has already influenced the field of condition monitoring. Dr. Xiang’s contributions are particularly notable for bridging the gap between theoretical deep learning models and practical, industry-ready diagnostic tools, making her a key figure in enhancing the safety and longevity of automated manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1