학술논문

Bearing Fault Detection in Adjustable Speed Drive-Powered Induction Machine by Using Motor Current Signature Analysis and Goodness-of-Fit Tests
Document Type
Periodical
Source
IEEE Transactions on Industrial Informatics IEEE Trans. Ind. Inf. Industrial Informatics, IEEE Transactions on. 17(12):8265-8274 Dec, 2021
Subject
Power, Energy and Industry Applications
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Fault detection
Variable speed drives
Vibrations
Optical sensors
Informatics
Windings
Time-frequency analysis
Bearing fault detection (BFD)
goodness-of-fit test (GoFT)
induction machine (IM)
probability distribution (PD)
Language
ISSN
1551-3203
1941-0050
Abstract
Induction machines are widely used in several industries around the world; their robust design allows them to operate even under nonoptimal conditions; the nonoptimal operation can reduce the machine lifetime depending on the anomaly magnitude; this leads to a loss of process efficiency, which eventually generates a considerable operational costs increment. Monitoring methods, that allow an early fault detection, are getting developed currently; these methods are focused on the fault detection of the main components of the machine; one of them is the bearing fault detection that can be obtained through the phase current signal analysis. In this article, three types of goodness-of-fit test are studied; in these methods, the motor current signature and the motor square current signature are analyzed. Furthermore, three types of bearing damage are presented and studied; the damages studied are: single point damage (bearing outer-race damage and bearing ball damage), and distributed damage (corrosion damage). The induction machine signals, when working with the damages mentioned before, are measured at two powering conditions: power grid sourced (at 60 Hz constant frequency), and adjustable speed drive (at six operating frequencies).