Utilizing data from a sensorless AC variable speed drive for detecting mechanical misalignments

Samieh Abusaad, Ahmed Benghozzi, Yimin Shao, Fengshou Gu, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)


Conventional condition monitoring techniques such as vibration, acoustic, ultrasonic and thermal techniques require additional equipment such as sensors, data acquisition and data processing systems which are expensive and complicated. In the meantime modern sensorless flux vector controlled drives can provide many different data accessible for machine control which has not been explored fully for the purpose of condition monitoring. In this paper polynomial models are employed to describe nonlinear relationships of variables available from such drives and to generate residuals for real time fault detection and performance comparisons. Both transient and steady state system behaviours have been investigated for optimal detection performance. Amongst 27 variables available from the drive, the torque related variables including motor current, Id, Iqcurrents and torque signals show changes due to mechanical misalignments. So only these variables are explored for developing and optimising detection schemes. Preliminary results obtained based on a motor gearbox system show that the torque feedback signal, in both the steady and transient operations, has the highest detection capability whereas the field current signal shows the least sensitivity to such faults.

Original languageEnglish
Title of host publicationDamage Assessment of Structures X
Editors Biswajit Basu
Number of pages8
Publication statusPublished - Jul 2013
Event10th International Conference on Damage Assessment of Structures - Dublin, Ireland
Duration: 8 Jul 201310 Jul 2013

Publication series

NameKey Engineering Materials
ISSN (Print)1013-9826


Conference10th International Conference on Damage Assessment of Structures
Abbreviated titleDAMAS 2013


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