Title :
Electro hydraulic servovalve health monitoring using fading extended Kalman filter
Author :
Loesch Vianna, Wlamir Olivares ; de Souza Ribeiro, Luiz Gonzaga ; Yoneyama, Takashi
Author_Institution :
EMBRAER S. A. São José dos Campos, Brazil
Abstract :
Hydraulic systems are one of the most common power source in both transport systems (i.e. aircrafts) and industrial systems. Electro hydraulic servovalves are critical components and often subjected to failures. This article presents a method to estimate degradation in a servovalve using an application of the Fading Extended Kalman Filter for system identification. A single failure mode related to nozzle blockage was considered. Evaluation of the degradation parameter noise value as well as the forgetting factor was done in order to correlate these values with the filter precision to estimate the degradation parameter. The conclusion elaborates on the capability of the proposed method to estimate the degradation, and procedures for both forgetting factor and degradation parameter noise selection.
Keywords :
Degradation; Delays; Estimation; Kalman filters; Mathematical model; Noise; Valves; Extended Kalman Filter; Fading; Health Monitoring; Hydraulic Servovalve;
Conference_Titel :
Prognostics and Health Management (PHM), 2015 IEEE Conference on
Conference_Location :
Austin, TX, USA
DOI :
10.1109/ICPHM.2015.7245033