Time Synchronized Distributed Acoustic Sensing of Partial Discharge at the Oil-Pressboard Interface

Distributed acoustic sensing (DAS) is a well-established technology used across a variety of industries. Due to its inherently low sample rates at detection ranges of a couple of hundred meters or more, at face value, it appears ineffective for partial discharge (PD) detection and therefore has not been previously used. However, in this publication, we show that aliasing effects due to the DAS sampling methods successfully downsample the higher-frequency acoustic emissions (AEs) and can provide detection of PD above 120 pC under treeing discharge across an oil–pressboard interface. This is supported by comparisons between DAS, high-sample rate acoustic sensors, as well as industry-standard electrical measurements. Synchronization between the different measurement systems is achieved allowing for sample-to-sample comparison as well as a more statistical approach. We additionally show that phase-resolved PD (PRPD) analysis can be applied to the DAS results with an additional voltage zero-crossing synchronization signal, with a clear resemblance to electrical methods.