Insulation failures prognosis in electric machines: preventive detection and time to failure forecast

Abstract

This work presents a new approach to the on-line evaluation of the insulation of electric machines. Through the proposed system, it is possible to identify the stress agents causing the degradation of the insulation of low-and mediumvoltage machines. In addition, the estimation of the time-to-failure (TF) of the insulation is developed based on linear stochastic models autoregressive moving average and artificial neural networks. The identification of the stress agent and the estimation of the TF give a complete prognosis for the predictive monitoring of the machine insulation.

Besisukančių elektros mašinų izoliacijos varžos matavimo metodų tyrimas

“…Elektros mašinos (EM) eksploatavimo trukmė apibrėžiama laikotarpiu, per kurį laikantis nustatytų eksploatavimo sąlygų ir atliekant profilaktinę priežiūrą, užtikrinamas patikimas jos veikimas. Eksploatavimo patirtis parodė, kad EM praranda savo funkcionalumą dažniausiai dėl izoliacijos nusidėvėjimo arba pažeidimo ir tokių gedimų tipai sudaro 30-40 % visų galimų gedimų mašinose (Armando and Sidelmo, 2020). EM izoliacijos nusidėvėjimą lemia įvairūs veiksniai (1 pav.).…”

Methods of Diagnosing the Insulation of Electric Machines Windings

“…Operational supervision includes the registration and viewing of the recorded operating parameters of the machine, that is, voltage, current, temperature (winding and the package of stator sheets, bearings), vibrations of bearing shields, correct operation of cooling and lubrication, and periodic measurements of insulation resistance [5]. Early detection of faults reduces repair costs and protects the machine against breakdown.…”

“…A significant number of failures, i.e., unexpected and unplanned stops of drives equipped with electrical machines, are caused by damage to the insulation system [3][4][5][6][7].…”