Comparing Extended Kalman Filter and Particle Filter for estimating field and damper bar currents in Brushless Wound Field Synchronous Generator for stator winding fault detection and diagnosis

Abstract

Condition monitoring of the Brushless Wound Field Synchronous Generator (BWFSG) is important as it iswidely used in mission and safety critical applications such as marine vessels. The frequency signatures in rotor field current are well known indicators to detect and diagnose stator winding short circuits in synchronous generators, in addition the damper bars current could also be used for fault detection and diagnosis. However, BWFSG these currents are not accessible. Hence, it is important to use the mathematical model and state estimation techniques to estimate these parameters. This paper compares the performance of state estimation techniques such as the Extended Kalman Filter (EKF) and Particle Filter (PF) in estimating field current and damper bars current for stator winding fault detection and diagnosis. The experimental validation results confirmed that the performance of the EKF is better than that of the PF in terms of number of stator winding fault signatures extracted from estimating the field current and damper bars currents. Thus, the future work proposed to use the EKF for developing Model-Based Condition Monitoring (MBCM) system for the BWFSG. NOMENCLATUREInstantaneous voltage Instantaneous current Inductance Resistance  Angular velocity of the rotor in rad/s Subscripts Leakage quantity Magnetizing quantity q-axis quantity d-axis quantity 0 Zero sequence quantity Stator quantity Rotor quantity Damper bar q-axis leakage quantity Rotor field d-axis leakage quantity Damper bar d-axis leakage quantity Superscript ′ Rotor quantity referred to the stator

Aplicações do filtro de partículas para observação de estados e estimação de parâmetros em sistemas dinâmicos não lineares multivariáveis

“…A filtragem de partículas é aplicada em diversas áreas, tal como em sistemas eletromecânicos (CHULAEE;ZARCHI;SABZEVARI, 2019;NADARAJAN et al, 2016), termoelétricos (CHENG et al, 2014;LIU, 2017), posicionamento de objetos (XU et al, 2018), índices ambientais (CHAKRABORTY et al, 2017), abrangendo diversas outras áreas.…”