A low-complexity method based on compressed sensing for long term field measurement of insulator leakage current

Field measurements of insulator leakage current are necessary for long term data storage for research purposes and condition-based maintenance. Long term monitoring and storage of actual waveform are required since the electrical activity on the insulator surface cannot be predicted in advance. This leads to the accumulation of large amount of data. One solution is to optimize the local storage space usage by implementing mathematical tools to eliminate noise and data with low information content. However, the method is computationally intensive and large scale deployment of devices based on such methods is costly. Proper condition-based maintenance cannot be guaranteed without large-scale use of monitoring devices in the field. Thus, the authors propose the use of an alternate low-complexity approach based on compressed sensing that addresses the issue of data size in field measurements. The compressed sensing based technique is perfectly suitable for large-scale deployment of leakage current measurement devices in the context of field monitoring in insulators. The method is structured to deploy low computational burden in the monitoring devices by shifting the entire computational load from the monitoring device in the field to the decoder at the central monitoring station. Different categories of field measured waveforms have been used to demonstrate the performance of the proposed method. It is expected that this paper will contribute to the development of efficient field monitoring devices in insulators.