A comparison between piezoelectric sensors applied to multiple Partial Discharge detection by advanced signal processing analysis

The development of sensors applied to failure detection systems for power transformers is a critical concern since this device stands out as a strategic component of the electric power system. Amongst the most issues is the presence of partial discharges (PD) in the insulation system of the transformer which can lead the device to total failure. Aiming to prevent unexpected damages, several PD monitoring approaches were developed. One of the most promising is the Acoustic Emission (AE) technique which captures the acoustic signals generated by PDs using piezoelectric sensors. Although many studies have proved the effectiveness of AE, most signal processing approaches are strictly related to the frequency analysis of PD signals, which can hide important information such as the repetition rate of the failure. This article presents a comparison between two types of piezoelectric transducers: the micro fiber composite (MFC) and the lead zirconate titanate (PZT). To ensure the detection of multiple PDs the time-frequency analysis was carried out by Short-time Fourier transform (STFT). Intending to compare the sensibility of the transducers, the AE signals were windowed, and the root mean square (RMS) value was extracted for each part of the signal. Results indicated that spectrogram and RMS analysis have great potential to detect multiple PD activity. Although MFC was 2 times more sensitive to PD detection compared with the PZT sensor, PZT presents a higher frequency response band (0 - 100 kHz) concerning MFC (80 kHz).