Detection of partial discharge signals in unknown noisy environment

Electrical partial discharge (PD) is an indication of the beginning of an electrical insulation problem. Unfortunately the PD signals usually are superposed by various continuous or pulse shaped interferences/disturbances (corona discharges, high frequency harmonics, ambient noises, etc.). In an unknown environment an adaptive filter can estimate a desirable random signal in the presence of an additive random noise from a noisy data input information. For the purpose of improving signal-to-noise ratio, an adaptive noise cancelling algorithm may be employed and it is possible to achieve a superior system performance compared to direct filtering of the received signal. A primary sensor receives an information bearing signal S(n), corrupted by uncorrelated additive noise V₀(n), and a reference sensor receives a noise V_t(n) that is uncorrelated with the signal S(n), but correlated with the noise V₀(n) in the primary sensor. The reference signal is processed by an adaptive filter. The information bearing signal S(n) is essentially unaffected by the adaptive noise canceller while the minimization of the power of the noise component of the system output will maximize the output signal-to noise ratio (SNR)