A Fuzzy-Based Approach for the Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor Drive

International audienceThis paper investigates the use of fuzzy logic for fault detection and diagnosis in a pulsewidth modulation voltage source inverter (PWM-VSI) induction motor drive. The proposed fuzzy technique requires the measurement of the output inverter currents to detect intermittent loss of firing pulses in the inverter power switches. For diagnosis purposes, a localization domain made with seven patterns is built with the stator Concordia current vector. One is dedicated to the healthy domain and the six others to each inverter power switch. The fuzzy bases of the proposed technique are extracted from the current analysis of the fault modes in the PWM-VSI. Experimental results on a 1.5-kW induction motor drive are presented to demonstrate the effectiveness of the proposed fuzzy approach

Induction Motor Stator Faults Diagnosis by a Current Concordia Pattern Based Fuzzy Decision System

International audienceThis paper deals with the problem of detection and diagnosis of induction motor faults. Using the fuzzy logic strategy, a better understanding of heuristics underlying the motor faults detection and diagnosis process can be achieved. The proposed fuzzy approach is based on the stator current Concordia patterns. Induction motor stator currents are measured, recorded and used for Concordia patterns computation under different operating conditions, particularly for different load levels. Experimental results are presented in terms of accuracy in the detection motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia patterns

BLEVE Fireball Effects in a Gas Industry: A Numerical Modeling Applied to the Case of an Algeria Gas Industry

This chapter presents the numerical modeling of the BLEVE (Boiling Liquid Expanding Vapor Explosion) thermal effects. The goal is to highlight the possibility to use numerical data in order to estimate the potential damage that would be caused by the BLEVE, based on quantitative risk analysis (QRA). The numerical modeling is carried out using the computational fluid dynamics (CFD) code Fire Dynamics Simulator (FDS) version 6. The BLEVE is defined as a fireball, and in this work, its source is modeled as a vertical release of hot fuel in a short time. Moreover, the fireball dynamics is based on a single-step combustion using an eddy dissipation concept (EDC) model coupled with the default large eddy simulation (LES) turbulence model. Fireball characteristics (diameter, height, heat flux and lifetime) issued from a large-scale experiment are used to demonstrate the ability of FDS to simulate the various steps of the BLEVE phenomenon from ignition up to total burnout. A comparison between BAM (Bundesanstalt für Materialforschung und –prüfung, Allemagne) experiment data and predictions highlights the ability of FDS to model BLEVE effects. From this, a numerical study of the thermal effects of BLEVE in the largest gas field in Algeria was carried out

Diagnosis of Speed Sensor Failure in Induction Motor Drive

International audienceA large number of adjustable – speed drives in industry and emerging applications such as automotive (EV or HEV) require high dynamic performances, robustness against parameter variation and also reliability. parameter detuning and mechanical speed sensor faults lead to a deterioration of the performances and even to instability. therefore condition monitoring is becoming mandatory in those sensitive applications. the objective of this contribution is to study the feasibility of detection and diagnosis of the mechanical speed sensor faults in an induction motor drive. using knowledge of the motor condition, the proposed technique based on fuzzy logic is applied to discriminate load and parameter variations from the speed sensor faults. both simulation and experimental results are presented in terms of accuracy in the detection of speed sensor faults and knowledge extraction feasibility

Direct torque control of induction motor with fuzzy stator resistance adaptation

International audienceA new stator resistance estimator using fuzzy logic is proposed. The input variables of the fuzzy logic identifier are the input and output of the low-pass (LP) filter used to integrate the back-emf. Simulation results, using Matlab-Simulink, comparing the fuzzy estimator and a classical integrator in a direct torque control (DTC) scheme prove the superiority of the novel approach. The stator flux locus is smoothed and therefore torque ripples are reduced

Fuzzy Detection and Diagnosis of Fault Modes in a Voltage-Fed Pwm Induction Motor Drive

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