Time Series RUL Estimation of Medium Voltage Connectors to Ease Predictive Maintenance Plans

Abstract

The ageing process of medium voltage power connectors can lead to important power system faults. An on-line prediction of the remaining useful life (RUL) is a convenient strategy to prevent such failures, thus easing the application of predictive maintenance plans. The electrical resistance of the connector is the most widely used health indicator for condition monitoring and RUL prediction, even though its measurement is a challenging task because of its low value, which typically falls in the range of a few micro-ohms. At the present time, the RUL of power connectors is not estimated, since their electrical parameters are not monitored because medium voltage connectors are considered cheap and secondary devices in power systems, despite they play a critical role, so their failure can lead to important power flow interruptions with the consequent safety risks and economic losses. Therefore, there is an imperious need to develop on-line RUL prediction strategies. This paper develops an on-line method to solve this issue, by predicting the RUL of medium voltage connectors based on the degradation trajectory of the electrical resistance, which is characterized by analyzing the electrical resistance time series data by means of the autoregressive integrated moving average (ARIMA) method. The approach proposed in this paper allows applying predictive maintenance plans, since the RUL enables determining when the power connector must be replaced by a new one. Experimental results obtained from several connectors illustrate the feasibility and accuracy of the proposed approach for an on-line RUL prediction of power connectors.