Classification of Faults in DTC Induction Machine using Wavelet Decomposition Method

Matrix Converter rather than voltage source inverter can be used as high-performance technique supplying electric motor in Direct Torque Control (DTC). DTC's most significant deficiency in induction motor, magnetic torque ripple, can be markedly reduced by appropriate space voltage-vectors whose influence on stator flux and electromagnetic torque in DTC of induction machine that uses Matrix Converter the subject of this work. DTC degrees of freedom were shown seriously limited by 60° flux sectors, thus division to twelve 30° sectors of flux-space vector hexagon is proposed. The increased Matrix Converter degrees of freedom were then extracted for DTC implementation.

This paper presents a new configuration for direct torque control (DTC) of six-phase induction motor (SPIM). In the proposed method, direct torque and flux control are applied to the SPIM using matrix converter with the conventional three-phase source as its input. The new DTC scheme for SPIM benefits the advantages of both DTC and matrix converter. The simulation results show the effectiveness of the proposed method in both dynamic and steady state response.

Extended Kalman filter (EKF) has been widely applied for sensorless direct torque control (DTC) in induction machines (IMs). One key problem associated with EKF is that the estimator suffers from computational burden and numerical problems resulting from high order mathematical models. To reduce the computational cost, a two-stage extended Kalman filter (TEKF) based solution is presented for closed-loop stator flux, speed, and torque estimation of IM to achieve sensorless DTC-SVM operations in this paper. The novel observer can be similarly derived as the optimal two-stage Kalman filter (TKF) which has been proposed by several researchers. Compared to a straightforward implementation of a conventional EKF, the TEKF estimator can reduce the number of arithmetic operations. Simulation and experimental results verify the performance of the proposed TEKF estimator for DTC of IMs.

Artificial neural network-based DTC of an induction machine with experimental implementation on FPGA

Phonocardiogram (PCG), the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram (ECG) is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automatically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to produce PCG intensity envelopes and separates that into four parts: the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over 93% correct in detecting the first and second heart sounds. The presented automatic segmentation algorithm using wavelet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.

<span>Multilevel inverter (MLI) is commonly utilized in direct torque control (DTC) for medium and high power applications. The additional voltage vectors generated by MLI can be manipulated to achieve the optimal selection for the inverter switching states in the DTC control systems. Previously, a review of DTC which focused more on the two-level inverter for induction motor as well as a review of the multilevel converter in industrial applications had been implemented individually. However, a review on DTC development in MLI was insufficient in both papers. Therefore, this paper aims to give a comprehensive review of the improvement of DTC via various MLI applications. It is reviewed according to the applicable multilevel inverter topologies in the DTC system. The comparison of DTC by using conventional and multilevel inverter is synthesized. Thus, this review paper will hopefully lead researchers in further research activities actively.</span>

In order to improve the recognition performance and solve the problem of computational complexity caused by the high-dimensional data in human identification, a gait recognition method based on manifold learning is proposed in this paper. Firstly, gait energy image (GEI) of a walking person is abstracted from a gait image sequence. And then discrete wavelet decomposition (DWT) and t-Distributed Stochastic Neighbor Embedding (t-SNE) method is applied to reduce the dimension of high-dimensional GEI data. Finally the support vector machine (SVM) models are trained by the decomposed feature vectors, and the gaits are classified by the trained SVM models at last. Experimental results show that the proposed feature extraction method is efficient in reducing computational complexity and preserving image information.

Direct torque control was introduced in 1980 for induction machine for torque and flux control and developed for MSAP in 1990. DTC is gaining popularity due to its simple control structure and easy implementation. The principle of direct torque control (DTC) of the asynchronous machine was introduced in 1985 by I. Takahashi as an alternative to flux-directed vector control (FOC). It is thanks to its simple control structure that it gains popularity and its easy implementation that it has opened a new horizon in the field of variable speed control of electric drives. Indeed, direct torque control (DTC) has benefited in recent years from significant methodological advances in operation and technological development following the introduction of power electronics and digital electronics and the implementation of possible and very usable control algorithms. In conjunction with these technological advances, the scientific community has developed several control approaches to control the operation of electrical machines. In this context, this article presents a comparative study of the different direct torque control (DTC) strategies and structures of the permanent magnet synchronous machine (MSAP). We propose the algorithm of this control making it possible to provide solutions to the ripples of the torque and the stator flux in order to reduce them by adopting a method of compensating the effects of progression by passing from the six sector DTC (DTC – 6S: classic and modified) then develop the twelve-sector DTC (DTC-12S) whose purpose is to minimize ripples and control the switching frequency of the inverter. The simulation graphs presented will clearly show the difference between the different controls techniques cited.

Faulty operation of direct torque control (DTC)-driven permanent magnet synchronous machine (PMSM) may result in an unstable drive system. Therefore, fault detection and classification become mandatory to maintain a safe and reliable operation in DTC-driven PMSMs. However, due to the nonlinear nature and tolerance capability of DTC, fault diagnosis is a challenging task in DTC drives. In this paper, the instantaneous active and reactive power signature analysis and support vector machine classifier are assessed with respect to the accuracy of fault detection, classification, and severity estimation in DTC-driven PMSMs. Three types of faults are investigated: inter-turn short circuit, local demagnetization, and high resistance contact. Numerical results demonstrate that the support vector machine classifier is capable of fault detection and classification for DTC-driven PMSMs with sufficient accuracy and limited training data.

The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

The effects on torque performance when using small voltage vectors of Matrix Converters is investigated in this paper. These vectors are used in order to reduce the electromagnetic torque ripple which appears when Direct Torque Control technique is used in Induction Motors. Direct Torque Control for Induction Motors using Matrix Converters is reviewed and it is pointed out the problem of the electromagnetic torque ripple which is one of the most important drawbacks of the Direct Torque Control. A new look-up table for Direct Torque Control using small vectors of Matrix Converters is developed. With the new look-up table, the system will differentiate between small and large torque errors and consequently reduce the electromagnetic torque ripple. A comparison between the classical Direct Torque Control using Matrix Converters and the proposed method is carried out. Results which demonstrate the improvement of the novel Direct Torque Control are shown.

In this paper, a design method of direct torque control (DTC) of an induction machine, which is based on fuzzy logic control (FLC), is proposed. The FLC which is introduced to improve the DTC uses a reduced number of fuzzy inference rules that facilitates the reduction of the FLC computation time. The improvement is performed by reducing the torque and stator flux ripples in the induction machine drive. Then, a hardware description that is based on the VHDL hardware description language of the proposed design is presented and discussed. The techniques of the parallel architecture, direct computation, and modular architecture are adopted for the design of the controller. Simulation and experimental results of the DTFC are compared with those of the conventional DTC. The comparison results illustrate the reduction in the torque and stator flux ripples of the DTFC. The validity of the proposed method is confirmed by the simulation and experimental results.

Direct Torque Control (DTC) has becoming the industrial standard for Induction Machine (IM) torque control by means of very simple control schemes. This paper presents a contribution for detailed comparison of Direct Torque Control strategies (Classical DTC, SVM-DTC and Fuzzy DTC) for Induction Machine. The performances of those various methodologies are evaluated and compared by simulation in terms of torque and current ripples, and transient response.

In this paper, a new direct torque control (DTC) algorithm for six phase induction machines (6PIM) when one phase is lost will be introduced. The machine has two sets of three phase windings spatially shifted by 60deg electrical degrees. A general decoupled model of the induction machine with up to four open phases is given. Fixed switching frequency and low torque ripple are obtained using this method. Simulation results show good dynamic and steady state performance. Experimental results are carried out to validate the proposed method.

A stator-flux-based direct torque control (DTC) of induction machine has shown significant interests to researchers since its offer several advantageous compared to many other control schemes. This scheme requires only one parameter which is a stator resistance in order to estimate the stator flux-linkage, hence the electromagnetic torque can be directly calculated. In practice, a wide variation in stator resistance can occur due to a large temperature variation. Thus, the mismatch between estimated and actual stator resistances will deteriorate the performance of DTC by introducing errors in the stator flux estimation particularly at low speed. Consequently, the torque performance will be degraded. This paper presents the study on stability and performances of DTC due to stator resistance variation. The effect on DTC performances due to the stator resistance variation will be analytically studied with the help of simulation results.