Gérard-André Capolino

Advances in Diagnostic Techniques for Induction Machines

This paper investigates diagnostic techniques for electrical machines with special reference to induction machines and to papers published in the last ten years. A comprehensive list of references is reported and examined, and research activities classified into four main topics: 1) electrical faults; 2) mechanical faults; 3) signal processing for analysis and monitoring; and 4) artificial intelligence and decision-making techniques.

A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection

Fault detection in alternating-current electrical machines that is based on frequency analysis of stator current has been the interest of many researchers. Several frequency estimation techniques have been developed and are used to help the induction machine fault detection and diagnosis. This paper presents a technique to improve the fault detection technique by using the classical multiple signal classification (MUSIC) method. This method is a powerful tool that extracts meaningful frequencies from the signal, and it has been widely used in different areas, which include electrical machines. In the proposed application, the fault sensitive frequencies have to be found in the stator current signature. They are numerous in a given frequency range, and they are affected by the signal-to-noise ratio. Then, the MUSIC method takes a long computation time to find many frequencies by increasing the dimension of the autocorrelation matrix. To solve this problem, an algorithm that is based on zooming in a specific frequency range is proposed with MUSIC in order to improve the performances of frequency extraction. Moreover, the method is integrated as a part of MUSIC to estimate the frequency signal dimension order based on classification of autocorrelation matrix eigenvalues. The proposed algorithm has been applied to detect a rotor broken bar fault in a three-phase squirrel-cage induction machine under different loads and in steady-state condition.

Diagnosis of Broken Bar Fault in Induction Machines Using Discrete Wavelet Transform without Slip Estimation

The aim of this paper is to present a wavelet-based method for broken bar fault detection in induction machines. The frequency-domain methods which are commonly used need speed information or accurate slip estimation for frequency components localization in any spectrum. Nevertheless, the fault frequency bandwidth can be well defined for any induction machine due to numerous previous investigations. The proposed approach consists in the energy evaluation of this known bandwidth with time-domain analysis using the discrete wavelet transform (DWT). Then, it has been applied to the stator current space vector magnitude and the instantaneous magnitude of the stator current signal for different broken bar fault severities and load levels.

Modeling and Control of Six-Phase Symmetrical Induction Machine Under Fault Condition Due to Open Phases

This paper introduces a new fault-tolerant operation method for a symmetrical six-phase induction machine (6PIM) when one or several phases are lost. A general decoupled model of the induction machine with up to three open phases is given. This model illustrates the existence of a pulsating torque when phases are opened. Then, a new control method reducing the pulsating torque and the motor losses is proposed in order to improve the drive performances. The proposed method is compared to two other existing techniques. The simulation and experimental results obtained on a dedicated test-rig confirm the validity and the efficiency of the proposed method for a fault-tolerant symmetrical 6PIM drive.

Fuzzy Logic and Sliding-Mode Controls Applied to Six-Phase Induction Machine With Open Phases

The faulted mode of a six-phase induction machine (6PIM) denotes that the motor is working with one or more missing phases. This situation leads to torque oscillations and poor tracking behavior. Therefore, the design of a suitable robust control is a challenging task. In this way, this paper presents the application of fuzzy logic and sliding mode controls in order to obtain a high-accuracy positioning of a 6PIM rotor in both healthy and faulted modes. The two control strategies are completely different from a theoretical point of view, but the final objectives are to remove the drawbacks of the specific fault on interest. The experimental results are obtained on a dedicated setup based on a 6PIM coupled with a variable mechanical load and for which up to three phases can be removed.

Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art

Recently, research concerning electrical machines and drives condition monitoring and fault diagnosis has experienced extraordinarily dynamic activity. The increasing importance of these energy conversion devices and their widespread use in uncountable applications have motivated significant research efforts. This paper presents an analysis of the state of the art in this field. The analyzed contributions were published in most relevant journals and magazines or presented in either specific conferences in the area or more broadly scoped events.

High Frequency Resolution Techniques for Rotor Fault Detection of Induction Machines

Motor current signature analysis (MCSA) is the reference method for the diagnosis of medium-large machines in industrial applications. However, MCSA is still an open research topic, as some signatures may be created by different phenomena, wherein it may become sensitive to load and inertia variations, and with respect to an oscillating load torque, although suitable data normalization can be applied. Recently, the topic of diagnostic techniques for drives and low to medium size machines is becoming attractive, as the procedure can be embedded in the drive at no additional thanks to a dedicated firmware, provided that a suitable computational cost is available. In this paper, statistical time-domain techniques are used to track grid frequency and machine slip. In this way, either a lower computational cost or a higher accuracy than traditional discrete Fourier transform techniques can be obtained. Then, the knowledge of both grid frequency and machine slip is used to tune the parameters of the zoom fast Fourier transform algorithm that either increases the frequency resolution, keeping constant the computational cost, or reduces the computational cost, keeping constant the frequency resolution. The proposed technique is validated for rotor faults.

Analytical approach of the stator current frequency harmonics computation for detection of induction machine rotor faults

The aim of this paper is to analyze theoretically and experimentally the stator current of a three-phase squirrel-cage induction machine in order to show how it is influenced by electrical rotor faults. The approach used for this study analyzes the modification introduced by n broken rotor bars in the rotor cage magnetomotive force and then estimates the resulting frequency spectrum in the stator current. This approach is validated in a 3-kW 230-V/400-V 50-Hz 2850-r/min two-pole three-phase induction machine, showing the sensitive frequency components to rotor fault condition.

Advanced Diagnosis of Electrical Faults in Wound-Rotor Induction Machines

The aim of this paper is to present a diagnosis methodology for the detection of electrical faults in three-phase wound-rotor induction machines (WRIMs). In the considered application, the rotor windings are supplied by a static converter for the control of active and reactive power flows exchanged between the machine and the electrical grid. The proposed diagnosis approach is based on the use of wavelet analysis improved by a preprocessing of the rotor-voltage commands under time-varying conditions. Thus, the time evolution of fault components can be effectively analyzed. This paper proves also the importance of the fault components computed from rotor voltages in comparison to those coming from rotor currents under closed-loop operation. A periodical quantification of the fault, issued from the wavelet analysis, has been introduced for accurate stator- or rotor-fault detection. Simulation and experimental results show the validity of the proposed method, leading to an effective diagnosis procedure for both stator and rotor electrical faults in WRIMs.

Fuzzy logic applied to speed control of a stepping motor drive

Nowadays, thanks to the development of microprocessors, stepping motors are widely used in robotics and in the numerical control of machine tools where they have to perform high-precision positioning operations. Nevertheless, the variations of the mechanical configuration of the drive, which are common to these two applications, can lead to a loss of synchronism for high stepping rates. Moreover, the classical open-loop speed control is weak and a closed-loop control becomes necessary. In this paper, the fuzzy logic principle is applied to control the speed of a stepping motor drive with feedback. An advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the fuzzy logic controller when variations of the mechanical configuration occur. The experiment has been performed using a low-cost 16 bit microcontroller in order to verify the design performance.