Inicio  /  Applied Sciences  /  Vol: 10 Par: 24 (2020)  /  Artículo
ARTÍCULO
TITULO

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

Álvaro Gómez-Pau    
Jordi-Roger Riba and Manuel Moreno-Eguilaz    

Resumen

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.

 Artículos similares

       
 
Yong Zhang, Xin Wang, Zongli Jiang, Junfeng Wei, Hiroyuki Enomoto and Tetsuo Ohata    
Arctic glaciers comprise a small fraction of the world?s land ice area, but their ongoing mass loss currently represents a large cryospheric contribution to the sea level rise. In the Suntar-Khayata Mountains (SKMs) of northeastern Siberia, in situ measu... ver más
Revista: Water

 
Jianzhao Liu, Liping Gao, Fenghui Yuan, Yuedong Guo and Xiaofeng Xu    
Soil water shortage is a critical issue for the Southwest US (SWUS), the typical arid region that has experienced severe droughts over the past decades, primarily caused by climate change. However, it is still not quantitatively understood how soil water... ver más
Revista: Water

 
Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León    
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc... ver más
Revista: Algorithms

 
Dimitris Fotakis, Panagiotis Patsilinakos, Eleni Psaroudaki and Michalis Xefteris    
In this work, we consider the problem of shape-based time-series clustering with the widely used Dynamic Time Warping (DTW) distance. We present a novel two-stage framework based on Sparse Gaussian Modeling. In the first stage, we apply Sparse Gaussian P... ver más
Revista: Algorithms

 
Nicholas V. Sarlis, Efthimios S. Skordas, Stavros-Richard G. Christopoulos and Panayiotis K. Varotsos    
Here, we employ natural time analysis of seismicity together with non-extensive statistical mechanics aiming at shortening the occurrence time window of the Kahramanmaras-Gazientep M7.8 earthquake. The results obtained are in the positive direction point... ver más
Revista: Applied Sciences