Original scientific paper

Motor Current Signature Analysis in Predictive Maintenance

Saša NIKOLIĆ ; Elmins doo NikoleTesle 99,89240 Gacko Bosnia and HerzegovinaElmins doo NikoleTesle 99,89240 Gacko Bosnia and Herzegovina
Radoš ĆALASAN ; Elmins doo NikoleTesle 99,89240 Gacko Bosnia and Herzegovina

Abstract

The aim of this paper is to draw attention to the possibilities offered by spectral analysis of current and voltage in the predictive maintenance of the
electric motor. Motor Circuit analysis (MCA) and Motor Current Signature analysis (MCSA) are innovative and non-invasive methods that enable
diagnostics and assessment of the condition of the electric motor. The main advantage of the method is that the test is carried out during the normal
motor operation, without downtime. All motor defects can be detected at the earliest stage. This enable planning the overhaul according to the
condition which can make significant savings. Advanced MCSA analysers enable diagnostics of electric motors that are powered either via a soft
starter, frequency inverter or directly from mains. So, it is possible in a simple and reliable way make an condition assessment of frequency inverters.
In addition, it is possible to detect faults of driven machine, like misalignment, imbalance, blade faults, belts, bearings issues etc. Theoretical basis
and tests that are carried out are explained in the paper

Keywords

Predictive maintenance; Spectral analysis; MCA; MCSA

Hrčak ID:

213518

URI

https://hrcak.srce.hr/213518

Publication date:

10.12.2018.

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