Stator Current Of Induction Motor Research Articles

Fuzzy current analysis-based fault diagnostic of induction motor using hardware co-simulation with field programmable gate array

Introduction. Presently, signal analysis of stator current of induction motor has become a popular technique to assess the health state of asynchronous motor in order to avoid failures. The classical implementations of failure detection algorithms for rotating machines, based on microprogrammed sequential systems such as microprocessors and digital signal processing have shown their limitations in terms of speed and real time constraints, which requires the use of new technologies providing more efficient diagnostics such as application specific integrated circuit or field programmable gate array (FPGA). The purpose of this work is to study the contribution of the implementation of fuzzy logic on FPGA programmable logic circuits in the diagnosis of asynchronous machine failures for a phase unbalance and a missing phase faults cases. Methodology. In this work, we propose hardware architecture on FPGA of a failure detection algorithm for asynchronous machine based on fuzzy logic and motor current signal analysis by taking the RMS signal of stator current as a fault indicator signal. Results. The validation of the proposed architecture was carried out by a co-simulation hardware process between the ML402 boards equipped with a Virtex-4 FPGA circuit of the Xilinx type and Xilinx system generator under MATLAB/Simulink. Originality. The present work combined the performance of fuzzy logic techniques, the simplicity of stator current signal analysis algorithms and the execution power of ML402 FPGA board, for the fault diagnosis of induction machine achieving the best ratios speed/performance and simplicity/performance. Practical value. The emergence of this method has improved the performance of fault detection for asynchronous machine, especially in terms of hardware resource consumption, real-time online detection and speed of detection.

Analysis and Approximation of THD and Torque Ripple of Induction Motor for SVPWM Control of VSI

This article presents a harmonic analysis of the stator currents of a squirrel-cage induction motor fed by a voltage source inverter with PWM space vector control (SVPWM). The influence of PWM switching frequency and dead time (dead band) of controlled transistors on THD and electromagnetic torque ripple is shown. The aim is to determine the lowest switching frequency of the transistors for which the drive will operate correctly. Characteristics were determined as functions in the form of THD (fPWM), where the least square approximation was used for stator current measurements when the PWM switching frequency was changed. The approximations were realized for simulation and experimental results. To clarify the results, the operation of hardware PWM circuits in microcontrollers is analyzed.

Behaviour of Rotating Field in Slip-Ring Induction Motors with Chopper Control.(Dept.E)

Stator currents of slip-ring induction motor having chopper control in the rotor circuit, are no more sinusoidal. The analysis of the air-gap resultant field , due to such currents , results in a different expression for the established rotating field. The derived expression is examined in order to study the rotating field behavior under chopper control. In addition to some of the well known behaviours , a new one had been distinguished and proved by constructing the geometrical pattern of the air-gap resultant field. An effective winding factor is introduced to give the effect of nonsinusoidal stator currents on the magnitude of the resultant m.m.f. harmonics.

ANFIS Based DTC SVPWM Controller for Induction Motor

This paper presents three PWM techniques, space vector PWM (SVPWM). SVPWM gives the more rms stator flux ripples in induction motor at 0.76 modulation indices, which gives more ripples in current and torque distortion. The flux performance of the induction motor is improved using three PWM (TPWM) due to twin switching transition with less area of rms stator flux ripple. The PI-control (PIC) doesn’t give the good dynamic performance of the induction motor drive using two level Voltage Source Inverter due to sudden changes in the load or speed. Further to improve dynamic performance in the torque and Flux of induction motor drive is simulated using type-2 fuzzy logic control (TP2FLC) and ANN in place of PIC because; TP2FLC and ANN is effectively dealing with uncertainties, and simulation results of speed, torque, flux and stator current of induction motor is compare with PIC of SVPWM and TPWM.

Time Delay Estimation Based Discrete-Time Super-Twisting Current Control for a Six-Phase Induction Motor

This article tackles the problem of high-accurate tracking of the stator currents of a six-phase induction motor in the presence of unknown dynamics such as unmeasurable rotor currents, parameter variation, and disturbances. Since the good features offered by sliding mode theory motivate the community of researchers on control, a time delay estimation based discrete-time super-twisting controller is proposed. First of all, an outer loop is carried out to regulate the speed and to generate the desired stator currents. Second, the inner loop, based on an indirect rotor field-oriented control, is executed based on the developed approach. The structure of the proposed method allows a precise approximation of the unknown dynamics and an accurate tracking and a fast convergence of the tracking error to a neighbor of zero. The design procedure and the stability analysis are detailed for the stator currents closed-loop system. Experimental tests have been performed on a six-phase induction motor to demonstrate the effectiveness of the developed discrete approach. In addition, the performances obtained are compared to the ones obtained using the discrete-time sliding mode with time delay estimation. The results obtained highlighted the satisfactory stator currents tracking performance in transient conditions and steady state and under different sampling times, parameters mismatch, and load and no-load conditions.

A Novel Speed and Current Sensor Fault-Tolerant Control Based on Estimated Stator Currents in Induction Motor Drives

The paper introduces a novel Fault Tolerant Control (FTC) algorithm based on estimated stator currents to diagnose some faulty states of stator current and speed sensors of Induction Motor (IM) drives. The FTC unit is integrated in the field-oriented control of induction motors to ensure that the IM drive can operate stably when current and speed sensor failures occur. The presented scheme combines two stator current estimators and a rotor speed estimator where a correction coefficient determined from the healthy current sensor is used to enhance the accuracy of the stator current estimation. To verify the capability of the proposed approach, the simulation in MATLAB-Simulink has been accomplished for various conditions of the IM drive, i.e. normal speed, low speed, and very low speed operating ranges. The results have confirmed very good features of the proposed FTC against the current and speed sensor fault in the different speed ranges.

Adaptive Predictive Current Control of Field-Oriented Controlled Induction Motor Drive

ABSTRACT An adaptive predictive current controller (APCC) for a direct field-oriented controlled (DFOC) three-phase asynchronous motor (AM) drive is implemented in this paper. Firstly, DFOC is implemented with conventional hysteresis current controller (HCC) and performance of HCC is being compared to that of the APCC. Stator current of induction motor (IM) is controlled using APCC according to the reference stator current produced by DFOC. An objective function defined in APCC is utilized to reduce the stator current error. The switching vector, which yields the least value of the objective function is opted and applied to the VSI. This controller does not need any linear regulators and modulation stage. Moreover, a stator resistance observer is also implemented to adapt to the change in the stator resistance. The dynamic performance of the machine under load torque, speed variations, and speed reversal are compared and analysed in MATLAB/Simulink and laboratory. The validation simulation results are made experimental results with dS1104. The fast dynamics response with respect to speed and torque, effective decoupling of flux and torque, robust operation of drive, and fast speed tracking are the benefits of the proposed APCC over classical HCC.

Dynamic Identification of Rotor Magnetic Flux, Torque and Rotor Resistance of Induction Motor

In the modern high-performance drive applications, a high-precision and efficient control of the induction motor depends on the accuracy of parameter values. However, the motor parameters may change due to the winding temperature fluctuations, flux saturation and skin effect. Any discrepancy between the values of the motor’s actual parameters and the ones used for the design of the controllers may result in degradation of the drive performance. In this work, a new identification method of hardly measurable internal quantities of the induction motor, such as components of the magnetic flux vector and electromagnetic torque, is outlined. Commonly, the measurable quantities of the induction motor like stator currents, stator voltage frequency and mechanical angular speed are used to determine a feedback effect of the rotor flux vector on the vector of the stator currents of induction motor. Based on this feedback, it is also possible to identify the actual value of the rotor resistance, which may alter during the induction motor operation. This has a significant impact on the precision of the identified quantities as well as on the master control of the induction motor. Stability of the identification structure is guaranteed by the position of roots of characteristic equation of its linear transfer function. Simulation and experimental results are given to highlight the quality, effectivity, feasibility, and robustness of the proposed identification method, which is working reliably within the whole range of the motor angular speed.

Implementation of PWM technique with soft starting algorithm for three-phase induction motor drives

In this paper, a study on issues related to starting of induction motor is carried out. Performance comparisons of various starting methods are also studied. To investigate the performance of ramp soft starting algorithm, sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) techniques are implemented with voltage source inverter (VSI) fed induction motor. Detailed FFT analysis of stator voltage and current of induction motor is studied under wide range of speed variations. Based on experimental study, few recommendations for implementation of boost start-up and s-curve start-up algorithm in Microcontroller (STM32F407VG) are made for high inertial load. Experimental results are obtained and its performance analysis in view of FFT of motor current is also carried out for aforesaid PWM techniques.

THE PHASE INDUCTION MOTOR STATOR EFFECTIVE CURRENT VALUE STARTUP MODE DEPENDENCE DETERMINATION

To determine the effective value of the stator current phase induction motor specialized techniques were developed. Phase current stator instantaneous values resulting arrays were obtained via an analog-to-digital converter L-Card. Phase stator current instantaneous arrays have been scanned from the original file by parsing. To implement the parsing string data used specialized Embarcadero Delphi class TParser. For obtaining average stator current values two algorithms were developed and presented. Obtaining extremums (minimums and maximums) of the sinusoidal signal were developed and presented. To make a measurement phase induction motor stator current used in current sensor Hall effect ACS712 Allegro 20A. To determine the phase stator effective current value based on instantaneous values of sinusoidal current signal array and filtering the output dataset was developed Windows application by using Embarcadero Delphi Community Edition IDE. An application interface is designed in the form of fixed windows. The time dependence between instantaneous values of stator phase current without and with filtering by using a digital filter presented here. Effective stator current value time dependence is given here. The analysis of the results is given. The results were compared with measurements by using the astatic voltmeter with accuracy measurements 0.5. For experimental investigations low power induction motor AIR56A4U3 was used. Three-dimensional dependences of electromechanical characteristics are given. The simulation results are presented in the form of graphs of the transient processes of the stator current of an induction motor. Theresults are plotted as graphs of the dependence of the current values of the stator phase current, which were calculated and investigated by using Microsoft Excel. Polynomial dependences of the current values of the stator phase current are also given in a form of Microsoft Excel diagram

Detection of Generalized-Roughness and Single-Point Bearing Faults Using Linear Prediction-Based Current Noise Cancellation

The dominant components in the stator current of a typical induction motor contain a substantial amount of information that is not related to bearing faults and can be considered as “ noise ” to bearing fault detection. The presence of the noise in the current signal creates the possibility of missed and false alarms. This paper develops a current noise cancellation method. When noise cancellation is used for recovering a desired signal, the distinguishing characteristics of both the desired signal and the noise need to be considered. Contrary to conventional current noise cancellation methods, “predictability” is considered as the distinguishing characteristic. Linear prediction theory with an optimum prediction order is applied to efficiently model the predictable components as noise. The developed method is able to efficiently cancel out the noise from the current signal. The information about the mechanical load level, the faulty part of the bearing, machine parameters, nameplate values, the current spectrum distribution, and the current data associated with the healthy bearing is not required in this method. Simulation and experimental results confirm the merits and effectiveness of the developed method to detect the bearing fault types through kurtosis and spectral analysis.

Real-time safety monitoring in the induction motor using deep hierarchic long short-term memory

The safety of industrial installations requires real-time monitoring of the occurrence of defects in induction machines that are widely used in this field. The implementation of this type of system typically needs to process a large amount of data provided by sensors and thus necessitates high computing mass, which complicates sensor utilization in real time. In this paper, we propose a hierarchical recurrent neural network by stacking two long short-term memory layers to form a single end-to-end network. Trained to establish complex temporal relations in raw time series signals. Those signals are directly provided by the sensors without any preprocessing or hand engineered features extraction. To train the network, we use the stator currents of a three-phase induction motor captured in a steady state. The currents represent several operation modes, which comprise the healthy and failed states with several types of mechanical defects, electrical defects, and combinations thereof. The experimental results were obtained using data from a real test bed to demonstrate the robustness and speed of the proposed approach for real-time monitoring of the operating status of an induction motor.

Recurrent Neural Network (RNN) Based Bearing Fault Classification of Induction Motor Employed in Home Water Pump System

In home appliances, the water pump is used to supply the water from a room to the other rooms. Defects of the waterpump are not distributing the water, inner stator winding short circuit, and bearing failure. In this paper, bearingfault detection of induction motor (IM) used in home water pump system is developed by using recurrent neuralnetwork (RNN) method. It is difficult to detect fault bearing of IM using a mathematical model. So that, a recurrentneural network (RNN) method is applied to solves this problem. These bearing faults classifications are based on IMstator current waveform. Bearing fault types are all normal (AN), front fault (FF), rear fault (RF), and all fault (AF).While, the detection process consist of three step. They are taking bearing fault data, features extraction, and RNNfault detection. The bearing fault data is taken from the stator currents of IM by using soundcard oscilloscopesoftware. Second step is features extraction process to obtain more bearing fault signs. In this step, stator currentsof IM is converted from time domain into frequency domain by using Fast Fourier Transform (FFT). Last stage isRNN model to clasify the bearing fault of IM. The effectiveness of proposed RNN method is clarified by using fourbearing fault types.

A new frequency analysis for diagnosis of bearing defects in induction motors using the adaptive lifting scheme of wavelet transforms

This work describes a novel and effective application of the adaptive wavelet transformfor the detection of bearing faults on induction motor stator current. This transform is based on athree-step nonlinear lifting scheme: a fixed prediction followed by a space-varying update and a noadditive prediction. This transformation technique is used in a diversity of applications in digitalsignal processing and the transmission or storage of sampled data (notably the compression of thesound, or physical measurements of accuracy). Many faults in induction motor have beenidentified as bearing defects, rotor defects and external defects. Experimental results confirm theutility and the effectiveness of the proposed method for outer raceway fault diagnosis under noload and full load conditions.

SVPWM for 3-phase 3-level Neutral Point Clamped Inverter Fed Induction Motor Control

<p>This paper gives Space Vector Pulse Width Modulation (SVPWM) for 3-phase 3-level Neutral Point Clamped (NPC) inverter fed induction motor control. A conventional two level inverter with 3-phase system has been developed for induction motor control. When it is applied for high voltage and power applications, which increases the voltage stress across the switch and harmonic content in the output. So multilevel inverter is much suitable for induction motor control, which provides nearly sinusoidal output voltage and diminished harmonic content in the output. Also the stator current of induction motor is minimsed, speed and torque of induction motor controlled with appropriate switching NPC inverter using SVPWM method. The proposed system simulation are verified using matlab simulink. </p>

Current Noise Cancellation for Bearing Fault Diagnosis Using Time Shifting

The stator current of a typical induction motor involves the supply fundamental and its harmonics existing before and after the presence of a bearing defect, and much of the information they contain is not related to the bearing defect. In this sense, they are basically noise to bearing fault diagnosis problem. This paper develops a current noise cancellation method using time shifting. Current residue is obtained by adding digital current signal to its own sample-delayed representation as an antinoise component. The amount of the sample delay is only dependent upon the supply frequency and the sampling rate. This amount is set to eliminate the supply fundamental and its odd multiple harmonics. After obtaining the current residue, through the spectral analysis of the envelope of the current residue, the characteristic fault frequencies for a defective bearing can be revealed. To show the superiority, the developed method is experimentally compared with three of the current-based methods in the literature. Experimental results for the defects in the outer raceway, the inner raceway, and the ball of a bearing verify the merits and effectiveness of the developed method.

Combined Discrete-time Sliding Mode and Disturbance Observer for Current Control of Induction Motors

This paper proposes a composite control strategy which combines a discrete-time sliding mode controller with a disturbance observer aiming to decouple current control of vector oriented induction motor drives. The stator current control is carried out through an indirect field orientation in a dq reference frame rotating at synchronous speed. The cross-coupling variables of the induction motor stator currents at synchronous reference frame are modeled as disturbances, and these values are estimated using a discrete-time disturbance observer. The digital implementation delay was included in the plant model formulation, resulting in a control law suitable to direct implementation in microcontrollers and digital signal processors. Then, the nominal and decoupled part of the induction machine model is used for the design of the sliding mode controller, and the additional variables are modeled as disturbances. The cross-coupling variables are observed and used in the control law. The convergence analysis is presented in discrete-time domain. Simulation and experimental results are presented to validate the theoretical analysis, and they show the good performance of the proposed method.

Synthesis and research of automatic balancing system of voltage converter fed induction motor currents

Synthesis of methods for investigating unbalanced operating conditions of thyristor voltage converter fed induction motors is performed. The voltage unbalance factors of the power source are calculated, and the formation conditions are determined. Attention is paid to the harmonic analysis of the induction motor currents. The influence of power source voltage unbalance on the induction motor performance is determined on the basis of simulation and experiments. The results of power source unbalance - phase current unbalance, overload capacity reduction, oscillating nature of torque and speed, dynamics deterioration are outlined. The system of automatic balancing of the induction motor stator currents using the thyristor voltage converter is proposed. The synthesis of the elements of control channels and feedback channels of the balancing system, as well as operation principles, are examined. It is determined that balancing reduces the current unbalance factors by more than an order of magnitude, and virtually ensures the equality of the active stator currents in the induction motor phases. The benefits and drawbacks of the automatic balancing system are presented, and recommendations on its application are given.

Braking mode simulation of induction motor of variable-frequency drive using stator current harmonics **

The work objective is to study electrodynamic processes in the frequency-controlled drive (FCD) by the mathematical modeling method, in particular, in the two-current mode of the dynamic braking considering the 5th and 7th current harmonics of the induction motor (IM) stator. The features of forming IM stator current low frequencies (0.2-15 Hz) by the autonomous voltage inverter (AVI) followed by the additional electricity loss in the FCD, and the appearance of torque ripple on the IM shaft causing jerkiness of the actuating mechanism (AM) of the production machine (PM) executive device (ED) in the low speed zone and complicating their locating in the prearranged position, are given. It is hard to implement the FCD scheduled deceleration without trajectory correction at the friction forces ambiguity in the ED AM mobility links and availability of the torque ripple on the IM shaft. To solve this problem, the authors offer, first, to use a spatial-vector pulse-width modulation (SV PWM) with m-fold submodulation of the carrier frequency (CF) and without submodulation in the IM braking mode. Secondly, it is reasonable to apply (momentarily in a low speed area) the principle of linearization by oscillation to reduce the K friction coefficient to a decreased value in the ED AM mobility links by the IM rotor microvibration due to the 5th and 7th harmonics of the stator current. Thus, the work on modeling FCD (in Matlab + Simulink software package) allows more accurately define the impact of the 5th and 7th harmonics of the IM stator current on the capability of the software implementation of the two-current mode of the FCD dynamic braking while reducing the total energy loss in the ED AM low-speed motion area. In addition, the applicability of the proposed solutions of the electric drives of mechatronic and robotic multipurpose systems with higher requirements for positioning in the basic AM - AVI circuits is confirmed.

Detection of rotor fault in three-phase induction motor in case of low-frequency load oscillation

This paper proposes a method for the separation of broken rotor bar failure and low-frequency load fluctuation in line-fed three-phase induction motor. In practice, the presence of load fluctuation at $$2sf_\mathrm{s}$$ has the same effect on a stator current of induction motor as a broken rotor bar fault. In such cases, the detection of broken rotor bar failure becomes difficult. To discern rotor fault and load oscillations, the analytical signal angular fluctuation (ASAF) method, which is a combination of Hilbert transform and the space vector angular fluctuation method, is used. The presented experimental results prove that low-frequency load oscillation and rotor fault can reliably be discriminated using the ASAF signal spectrum.