Work

Uncertainty variations and quantification of motor bearing time-varying resistance–capacitance characteristics

Year: 2025

Type: article

Abstract: During the operation of generators and drive motors, current breakdown conduction through bearings can cause electrical erosion, thereby reducing motor reliability and performance. This phenomenon results from mode-switching between the resistance–capacitance (RC) characteristics of the bearing. However, the transient variations of these time-varying RC characteristics remain insufficiently understood. To elucidate the uncertainty variation laws of bearing time-varying RC characteristics under realistic motor operating conditions, this study analyzes more than ten million bearing current breakdown conduction events across over five thousand transient and steady-state motor operating conditions. The influences and mechanisms of four key motor operating parameters—rotation speed, torque, rotation speed change rate, and torque change rate—on the time-varying RC characteristics (including equivalent resistance, equivalent capacitance, and RC mode-switching frequency) are systematically investigated. Based on these analyses, the boundary conditions of RC mode-switching are redefined, and a mixture density network is employed to model the mixed probabilistic distributions of RC characteristic parameters. Accordingly, a constitutive modeling framework based on interpretable descriptor surrogate models is developed to quantitatively characterize and probabilistically predict the uncertainty variations of bearing time-varying RC characteristics under both transient and steady-state operating conditions. This framework achieves high predictive accuracy while maintaining interpretability, simplicity, reliability, and generalizability. The proposed approach provides a theoretical foundation and modeling framework for the design and optimization of motor and bearing systems, offering potential strategies to suppress bearing currents and mitigate electrical erosion in generators and drive motors.

Source: Mechanical Systems and Signal Processing

DOI: 10.1016/j.ymssp.2025.113773

Authors: Zongxin Xiao, Minghui Hu, Chengmou Li, Shuang Chen, Guangyao Zhu

Institutions: Chongqing University, State Key Laboratory of Mechanical Transmission

Language: English

Topic: Electromagnetic Compatibility and Noise Suppression

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,730