Vacuum Circuit Breaker Closing Time Key Moments Detection via Vibration Monitoring: A Run-to-Failure Study

TL;DR

This study presents a vibration-based method to monitor vacuum circuit breaker closing times using a non-intrusive sensor, enabling continuous online condition monitoring and predictive maintenance through run-to-failure experiments.

Contribution

It introduces a novel algorithm utilizing short-time energy of vibration signals to infer closing times non-intrusively, validated on a large dataset from accelerated life testing.

Findings

The algorithm accurately detects key moments in VCB operation.

Vibration monitoring can replace intrusive measurements for condition assessment.

The dataset and method support future predictive maintenance strategies.

Abstract

Circuit breakers (CBs) play an important role in modern society because they make the power transmission and distribution systems reliable and resilient. Therefore, it is important to maintain their reliability and to monitor their operation. A key to ensure a reliable operation of CBs is to monitor their condition. In this work, we performed an accelerated life testing for mechanical failures of a vacuum circuit breaker (VCB) by performing close-open operations continuously until failure. We recorded data for each operation and made the collected run-to-failure dataset publicly available. In our experiments, the VCB operated more than 26000 close-open operations without current load with the time span of five months. The run-to-failure long-term monitoring enables us to monitor the evolution of the VCB condition and the degradation over time. To monitor CB condition, closing time is one of the indicators, which is usually measured when the CB is taken out of operation and is completely disconnected from the network. We propose an algorithm that enables to infer the same information on the closing time from a non-intrusive sensor. By utilizing the short-time energy (STE) of the vibration signal, it is possible to identify the key moments when specific events happen including the time when the latch starts to move, and the closing time. The effectiveness of the proposed algorithm is evaluated on the VCB dataset and is also compared to the binary segmentation (BS) change point detection algorithm. This research highlights the potential for continuous online condition monitoring, which is the basis for applying future predictive maintenance strategies.