Y Lei, J Lin, MJ Zuo, Z He - Measurement, 2014 - Elsevier
Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique behaviors, which invalidate fault diagnosis methods working well for fixed-axis gearboxes …
ME Orchard, GJ Vachtsevanos - Transactions of the Institute …, 2009 - journals.sagepub.com
This paper introduces an on-line particle-filtering (PF)-based framework for fault diagnosis and failure prognosis in non-linear, non-Gaussian systems. This framework considers the …
This paper presents a methodology for uncertainty quantification and model validation in fatigue crack growth analysis. Several models–finite element model, crack growth model …
M Orchard, G Kacprzynski, K Goebel… - … on prognostics and …, 2008 - ieeexplore.ieee.org
Particle filters (PF) have been established as the de facto state of the art in failure prognosis. They combine advantages of the rigors of Bayesian estimation to nonlinear prediction while …
Q Han, T Wang, Z Ding, X Xu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Stator current modeling for defective planetary gearboxes based on magnetic equivalent circuits (MEC) is conducted in this article. A lumped parameter torsional model of the motor …
Y Lei, J Lin, Z He, D Kong - Sensors, 2012 - mdpi.com
Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes …
L Hong, JS Dhupia, S Sheng - Mechanism and Machine Theory, 2014 - Elsevier
Equally spaced planetary gearboxes are important power-train components for varied engineering systems. Their failures can result in significant capital losses and pose safety …
J Yoon, D He, B Van Hecke - IEEE transactions on industrial …, 2015 - ieeexplore.ieee.org
Planetary gearboxes (PGBs) are widely used in the drivetrain of wind turbines. Any PGB failure could lead to breakdown of the whole drivetrain and major loss of wind turbines …
M Gwak, MS Kim, JP Yun… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Robustness of neural network models is important in fault diagnosis (FD) because uncertainty in operating conditions varies the power spectral densities of vibration data; …