Open AccessA robust diagnosis method for speed sensor fault based on stator currents in the RFOC induction motor drive
Author(s) -
Cuong Dinh Tran,
Pavel Brandštetter,
Minh Chau Huu Nguyen,
Sang Ho,
Bach Hoang Dinh,
Phuong Nhat Pham
Publication year - 2020
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v10i3.pp3035-3046
Subject(s) - stator , computer science , control reconfiguration , fault (geology) , control theory (sociology) , induction motor , controller (irrigation) , rotor (electric) , noise (video) , reliability (semiconductor) , electronic speed control , signal (programming language) , fault detection and isolation , matlab , engineering , embedded system , artificial intelligence , control (management) , power (physics) , electrical engineering , actuator , agronomy , programming language , physics , quantum mechanics , voltage , seismology , geology , image (mathematics) , biology , operating system
A valid diagnosis method for the speed sensor failure (SSF) is an essential requirement to ensure the reliability of Fault-Tolerant Control (FTC) models in induction motor drive (IMD) systems. Most recent researches have focused on directly comparing the measured and estimated rotor speed signal to detect the speed sensor fault. However, using that such estimated value in both the fault diagnosis and the controller reconfiguration phases leads to the insufficient performance of FTC modes. In this paper, a novel diagnosis-technique based on the stator current model combined with a confusion prevention condition is proposed to detect the failure states of the speed sensor in the IMD systems. It helps the FTC mode to separate between the diagnosis and reconfiguration phases against a speed sensor fault. This proposed SSF diagnosis method can also effectively apply for IMs’ applications at the low-speed range where the speed sensor signal often suffers from noise. MATLAB/Simulink software has been used to implement the simulations in various speed ranges. The achieved results have demonstrated the capability and effectiveness of the proposed SSF method against speed sensor faults.