Induction Motors Fault Detection Using Square-Root Transformed Cubature Quadrature Kalman Filter

2019 ◽  
Vol 34 (2) ◽  
pp. 870-877 ◽  
Author(s):  
Jafar Zarei ◽  
Elham Kowsari ◽  
Roozbeh Razavi-Far
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Induction Motors ◽  
Square Root

Applying GP-EKF and GP-SCKF for non-linear state estimation and fault detection in a continuous stirred-tank reactor system

2016 ◽  
Vol 39 (10) ◽  
pp. 1486-1496 ◽  
Author(s):  
Elham Kowsari ◽  
Behrooz Safarinejadian
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Gaussian Process ◽  
Stirred Tank ◽  
Square Root ◽  
Continuous Stirred Tank Reactor ◽  
Tank Reactor ◽  
Cubature Kalman Filter ◽  
Non Linear ◽  
Continuous Stirred Tank

This paper proposes two novel methods for fault detection in non-linear processes. These methods apply a Gaussian process (GP) to model the underlying process, and then the extended Kalman filter (EKF) and square root cubature Kalman filter (SCKF) are used to detect faults. Accordingly, two approaches called the Gaussian process–extended Kalman filter (GP-EKF) and Gaussian process–square root cubature Kalman filter (GP-SCKF) are proposed. The most important characteristic of these proposed methods is that there is no need for an accurate model of the system. Therefore, these methods are considered non-parametric approaches of fault detection in non-linear systems. To illustrate the performance of these algorithms in fault detection, they have been used in a continuous stirred-tank reactor system (CSTR). Both proposed methods are able to detect sensor faults at an early stage.

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Teymoor Ghanbari ◽  
Haidar Samet
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
High Performance ◽  
Induction Motors ◽  
Simple Technique ◽  
Harmonic Distortion ◽  
Stator Current ◽  
Three Phase ◽  
Power Frequency ◽  
Faults Diagnosis

AbstractMonitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Square-Root Cubature Kalman Filter and Its Application to SLAM of an Mobile Robot

ROBOT ◽  
2013 ◽  
Vol 35 (2) ◽  
pp. 186 ◽  
Author(s):  
Yifei KANG ◽  
Yongduan SONG ◽  
Yu SONG ◽  
Deli YAN ◽  
Danyong LI
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Square Root ◽  
Cubature Kalman Filter

Fault Detection of Induction Motors Using Just In Time Classifiers

2021 ◽  
Author(s):  
Saaeede Hazbavi ◽  
Roozbeh Razavi-Far ◽  
Mohammad Mehdi Arefi ◽  
Alireza Khayatian ◽  
Mehrdad Saif
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Just In Time
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