Fault detection and diagnosis in an induction machine drive: a pattern recognition approach based on Concordia stator mean current vector

Abstract

Abstract-The aim of this paper is to study the feasibility of fault detection and diagnosis in a three-phase inverter feeding an induction motor. The proposed approach is a sensor-based technique using the mains current measurement. A localization domain made with seven patterns is built with the stator Concordia mean current vector. One is dedicated to the healthy domain and the last six are to each inverter switch. A probabilistic approach for the definition of the boundaries increases the robustness of the method against the uncertainties due to measurements and to the PWM. In high-power equipment where it is crucial to detect and diagnose the inverter faulty switch, a simple algorithm compares the patterns and generates a Boolean indicating the faulty device. In low-power applications (less than 1 kW) where only fault detection is required, a radial basis function (RBF) evolving architecture neural network is used to build the healthy operation area. Simulated experimental results on 0.3-and 1.5-kW induction motor drives show the feasibility of the proposed approach.

Condition Monitoring of Induction Motors Based on Stator Currents Demodulation

“…Several papers have proposed to monitor the deviation of the analytic signal from a circle in the complex plane [53][54]. This approach holds when the stator current is amplitude modulated but is not appropriate when the stator current is frequency modulated since the fault only affects the rotational speed in the complex plane [7].…”

Identification of Open-Switch and Short-Switch Failure of Multilevel Inverters through DWT and ANN Approach using LabVIEW

“…Some researchers used the inverter current [8][9] and inverter output voltage [11][12][13][14][15] to develop the fault diagnostic system. Surin Khomfoi et al [13], developed an open-switch fault diagnostic system of a multilevel inverter using the output voltage FFT pattern and five parallel neural networks with 40 input neurons per network.…”

“…In industrial applications, where safe and reliable operation is always expected, it is important to monitor the condition of power electronic switches in inverters. As the number of level increases, number of power electronic switches also increases which leads to increase in probability of failure of any switch and hence any such fault should be detected at the earliest in order to avoid the operation of drive and motor under abnormal conditions [4][5][6][7][8][9][10][11][12][13][14].…”

Open Switch Fault Diagnosis in Three Phase Inverter Using Diagnostic Variable Method

“…In this method Fourier coefficients of current signal are used for fault diagnosis. In [6] and [7], neural network is used. This neural network is trained with the seven fault patterns which are calculated by average current Concordia vector trajectory.…”