Open AccessCurrent Sensor Fault Detection and Isolation in Doubly Fed Induction Generator
Author(s) -
Sushmita Kumari,
C. Priya
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2007/1/012045
Subject(s) - fault detection and isolation , isolation (microbiology) , current sensor , observer (physics) , control theory (sociology) , fuzzy logic , doubly fed electric machine , fault (geology) , computer science , reliability (semiconductor) , grid , induction generator , generator (circuit theory) , power (physics) , control engineering , engineering , ac power , current (fluid) , mathematics , electrical engineering , control (management) , artificial intelligence , wind power , voltage , actuator , biology , geometry , quantum mechanics , physics , microbiology and biotechnology , seismology , geology
Fault Detection and Isolation (FDI) is gaining interest as a means to increase the reliability and availability of efficient systems. Measuring sensors used for data acquisition are more prone to failures. The main objective of this paper is to provide model based FDI for current sensor fault closed-loop controlled Doubly Fed Induction Generator (DFIG) model connected to power grid. The sensor fault was detected and isolated by two methods including Unknown Input Observer (UIO) on reduced order DFIG model and fuzzy logic. The results show improvement in computational speed during online monitoring when the fault isolation is performed on reduced order models.