Acta Electrotechnica et Informatica, Vol. 17, No. 1, 2017, 49–57, DOI:10.15546/aeei-2017-0007 49 ISSN 1335-8243 (print) © 2017 FEI TUKE ISSN 1338-3957 (online), www.aei.tuke.sk SPEED SENSOR FAULTS DIAGNOSIS IN AN INDUCTION MOTOR VECTOR CONTROLLED DRIVE Mohamed BOUAKOURA * , Nasreddine NAÏT-SAÏD ** , Mohamed-Said NAÏT-SAÏD *** LSP-IE Laboratory, Electrical Engineering Department, Faculty of Technology, University of Batna 2, 05000 Batna, Algeria, * Tel.: +213 56 036 5608, * E-mail: bouakouramohamed@gmail.com ** Tel.: +213 55 929 2164, ** E-mail: n_naitsaid@yahoo.com *** Tel.: +213 77 368 8980, *** E-mail: medsnaitsaid@yahoo.fr ABSTRACT Many induction motor speed controllers contain a speed or position sensor. This last is required to provide accurate measurement. A faulty speed sensor decreases the controller performance dramatically. Hence, a fault diagnosis and detection technique is necessary. This paper deals with several faults which affect the speed sensor used in an induction motor vector controlled drive. Three different faults are considered; offset fault, uncertainty of measurement, and total loss of feedback information. Then a detection strategy is suggested based on the computation of the energy of the average standard deviation of speed data. Simulation on Matlab/Simulink and experiments were carried out to show the effect of each fault on the vector control performance and to verify the effectiveness of the proposed detection scheme. Keywords: speed sensor fault, induction motor, field oriented control, average standard deviation, energy of a signal 1. INTRODUCTION Sensors are devices that transform a physical signal to an electrical one (usually a current or voltage). The use of these elements is unavoidable in most engineering applications, especially for monitoring and control. They provide calculators with the necessary data for decision making. In different fields, such as industry and transportation, having reliable sensors is mandatory. However, these sensors are prone to many faults, which may affect the system performance. Usually, speed control requires speed or position sensors. In induction machine vector control schemes, the accuracy of the speed sensor signal is crucial. This component may undergo several faults which can be listed in four major types as follows:  Constant faults in which the sensor’s signal remains constant despite the variation of the rotor position [1, 2].  Bias, offset and excessive noise due to measurement considered as additional faults [2– 12].  Gain fault where the encoder signal is amplified [13].  Intermittent or total loss of feedback information [14–24]. In tachometric sensors, either DC generators or alternators, the intermittent fault is usually due to rotor eccentricity [15, 25] or attrition of the brushes or bearings. Whereas the variation of electrical parameters, such as resistances and inductances, in some operating conditions produces offset faults. Note that, the loss of feedback signal may occur due to electrical link disconnection or the breakdown of the sensor. Besides, the weakness of the light source (LED) or the degradation of the phototransistor in rotary encoders causes uncertain measurements [2, 15]. In both types of sensors, the mechanical sliding of the encoder can also cause an inaccuracy of measurement. Such faults do not cause an immediate change in average speed, but a significant change in its standard deviation [23]. Some experts designed robust encoders with the ability to maintain acceptable functionality despite their faulty state [26]. Yet, more researches are being conducted to detect and isolate speed sensor faults. The classical way to detect any malfunction implies hardware redundancy [27], so the signals of the faulty sensors and the healthy ones are compared to generate fault indicators. But since the advent of electronic calculators, model based methods gained more interest. This brought forward the concept of analytical redundancy where virtual sensors (estimators, filters, observers) such as Kalman filter, Luenberger observer and MRAS estimate the speed signal from other available measurements [1–5, 8–15, 17–20, 22, 28–30]. Moreover, two recent sets of techniques have been developed. The first one is based on signal processing, such as wavelet packet decomposition [15, 31] [15, 35], hodographs [32], adaptive thresholds [33], least squares regression [6], parity space [21] and average standard deviation [23]. The second one involves machine learning techniques such as fuzzy logic [34, 35], artificial neural networks [24] and genetic algorithms [32]. This paper investigates the effect of speed sensor faults on the induction machine control, and then it suggests a new detection approach. The advantage of this last resides in its low cost, simplicity of implementation and efficiency. The paper is organized as follows. Firstly, an introduction presenting a literature review on the subject. Section two is dedicated to field oriented control of the induction motor. Three speed sensor faults are explained in section three. Simulation results are shown in section four, while a detection technique is suggested in the fifth section. The experimental results of speed sensor faults and their detection are shown in section six. At last, a conclusion is presented in section seven. 2. INDIRECT FIELD ORIENTED CONTROL OF THE INDUCTION MOTOR Vector control by rotor flux orientation is a widely used and an effective technique. Its aim is the separate