D'Elia Gianluca; Cocconcelli Marco; Strozzi Matteo; Mucchi Emiliano; Dalpiaz Giorgio; Rubini Riccardo Motor current cyclic-non-stationarity analysis for bearing diagnostic (Conference) Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics, 2020, ISBN: 978-908289311-3. (Abstract | BibTeX | Tag: Cocconcelli M., D'Elia G., Dalpiaz G., Mucchi E., Rubini R., Strozzi M.) @conference{D'Elia2020,
title = {Motor current cyclic-non-stationarity analysis for bearing diagnostic},
author = {D'Elia Gianluca; Cocconcelli Marco; Strozzi Matteo; Mucchi Emiliano; Dalpiaz Giorgio; Rubini Riccardo},
editor = {KU Leuven - Departement Werktuigkunde},
isbn = {978-908289311-3},
year = {2020},
date = {2020-09-07},
booktitle = {Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics},
pages = {597 - 607},
abstract = {The Motor Current Signature Analysis (MCSA) is a research area focused on the diagnosis of components of electric motors based on post-processing of the current signal mainly. In particular, the bearing diagnostics is based on two different assumptions: the fault on the bearing causes a vibration of the shaft it supports, so there is an air gap variation between stator and rotor causing a modulation in the current signal; the fault on the bearing hinders the rotation of the shaft, so it can be modeled as an additional loading torque that the motor satisfies increasing the current signal. In this paper, a cyclic-non-stationarity analysis of the motor current is used to assess the status of ball-bearings in servomotors, running at variable speed. Both speed of the motor and motor current are provided by the control loop of the servomotor, that is no external sensors are used. The cyclic nature of the application allows an average of the cyclic-cyclic order maps to increase the signal-to-noise ratio. The proposed technique is successfully applied to both healthy and faulty bearings. },
keywords = {Cocconcelli M., D'Elia G., Dalpiaz G., Mucchi E., Rubini R., Strozzi M.},
pubstate = {published},
tppubtype = {conference}
}
The Motor Current Signature Analysis (MCSA) is a research area focused on the diagnosis of components of electric motors based on post-processing of the current signal mainly. In particular, the bearing diagnostics is based on two different assumptions: the fault on the bearing causes a vibration of the shaft it supports, so there is an air gap variation between stator and rotor causing a modulation in the current signal; the fault on the bearing hinders the rotation of the shaft, so it can be modeled as an additional loading torque that the motor satisfies increasing the current signal. In this paper, a cyclic-non-stationarity analysis of the motor current is used to assess the status of ball-bearings in servomotors, running at variable speed. Both speed of the motor and motor current are provided by the control loop of the servomotor, that is no external sensors are used. The cyclic nature of the application allows an average of the cyclic-cyclic order maps to increase the signal-to-noise ratio. The proposed technique is successfully applied to both healthy and faulty bearings. |
