Induction Motor Test Research Articles

The Design of Software for Three-Phase Induction Motor Test System

The design and development of control system software is important to three-phase induction motor test equipment, which needs to be completely familiar with the test process and the control procedure of test equipment. In this paper, the software is developed according to the national standard (GB/T1032-2005) about three-phase induction motor test method by VB language. The control system and data analysis software and the implement about motor test system are described individually, which has the advantages of high automation and high accuracy.

An investigation of the influence of bearing failures on the efficiency of an induction motor

The influence of the technical condition of bearings on the efficiency of induction motors (IMs) with a squirrel-cage rotor was considered. The experiments were carried out using induction-motor tests in the rated nominal regime with one operable bearing and two faulty ones, which had defects of the outer and inner parts. The bearing defects increase the energy loss, which leads to increased heat dissipation in the contact zone of its components, overheating, and reduction of motor efficiency. More accurate data on changing the efficiency of IMs with faulty bearings taking into account the heated state of the machine that is close to actual operating conditions were obtained. Thermal-imaging inspection of motor was performed, the graphic data characterizing the changes of temperatures of units and the machine efficiency when operating with a faulty bearing are presented. A diagnostic technique of the bearing condition by means of integral parameters of vibration acceleration that makes it possible to analyze the potential defects taking into account the weak level of their activation and the shift over the frequency response is considered.

Taxonomy of Induction-Motor Mechanical-Fault Based on Time-Domain Vibration Signals by Multiclass SVM Classifiers

In the present work, faults in induction motors (IM) have been diagnosed by multiclass support vector machine (SVM) algorithms based on time domain vibration signals. The main focus is to classify mechanical faults of induction motors, i.e. the bearing fault, unbalanced rotor, bowed rotor and rotor misalignment at different rotational speeds and diverse loading conditions. In this work, an induction motor test setup was used to generate vibration signals of seeded mechanical faults. For the effective fault diagnosis, one-versus-one multiclass SVM approach with the Gaussian-radial basis function (RBF) kernel has been used. For the fault classification, firstly optimum statistical features from higher statistical moments have been selected. Also the selection of SVM kernel parameters, numbers of feature datasets and optimum ratio of training-to-testing data have been performed. The SVM classifier is trained and tested at the same rotational speeds as the measured data as well as innovatively tested at intermediate rotational speeds for which measured data was not available. It is observed that classification accuracy gradually increases with the increase of the rotational speed and with the increase of the load on the IM.

A flexible filter for synchronous angular resampling with a wireless sensor network

Abstract Many tasks in the context of data acquisition with a wireless sensor network, e.g. angular resampling or jitter compensation, can be solved by reconstructing a uniformly sampled signal from a nonuniformly sampled one. A filter structure that is capable of performing this task has been adopted from the literature. It has been implemented in fixed-point arithmetic on a wireless sensor node. Compared to a floating-point implementation, this fixed point implementation has been shown to provide the same signal quality at only about one-tenth of computation time. Furthermore, it has been proven to be suitable for real-time operation on a resource constraint wireless sensor node. The implementation has been tested for the application example of synchronous angular resampling, but it can also easily be used in other resampling applications. Experiments with simulated data, a waveform generator and at an induction motor test bench show that the implemented filter is effective in resampling signals over a wide range of speeds and speed changes. In all cases its signal quality in terms of amplitude and frequency accuracy is at least as good that obtained using sample-and-hold resampling and surpasses it clearly in terms of signal-to-noise and distortion ratio (SINAD).

Induction machine bearing fault diagnosis based on the axial vibration analytic signal

This paper deals with a new induction motor defects diagnosis using the Axial Vibration Analytical Signal (AVAS). The signal is generated by a bearing-defected induction machine. The calculation method may be divided into two main parts; the former is the Hilbert transform that consists in the first part normalization of the axial vibration and its comparison with the AVAS module. The second part consists in the extraction of feature vectors using the Signal Class Dependent Time Frequency Representation (TFRSCD) based on the Fisher contrast design of the non parametrically kernel. The Particle Swarm Optimization (PSO) is used to optimize the feature vectors size. The vibration severity caused by the bearing fault is investigated for different loads. This last decreases with the increasing level of the load. The obtained results are experimentally validated on a 5500 W induction motor test bench.

LabVIEW Based Laboratory Typed Test Setup for the Determination of Induction Motor Performance Characteristics

Induction motors are widely used due to their rugged, robust and easy to care features. Since they are heavily used in industry, testing of three phase induction motors have play a vital role. In order to determine motor equivalent circuit parameters, efficiency of motor, squirrel caged laboratory sized an induction motor test setup is prepared. It is suitable for the induction motor with the frame size of 100 and 112. A virtual Instrumentation typed engineering workbench (called as LabVIEW) software packet, is utilized as a graphical user interface program. Motor input power is measured by measuring the input voltage, current and power factor with the help of hall effect typed voltage and current transformers. Also, the output power is measured by measuring the speed and torque with the help of an encoder and torque sensor. All outputs of the voltage and current transformer, encoder and temperature, torque sensors are given to the Data Acquisition Card (DAQ) which acquires the data for processing and then the equivalent circuit parameters, efficiency, performance and loading characteristics are found out, using LabVIEW based user interface. It is suggested to use this test rig for the quality control of produced motors in industry, and an educational experiment setup in the school laboratories.

A Vibration-Based Approach for Stator Winding Fault Diagnosis of Induction Motors: Application of Envelope Analysis


 
 
 Induction motors are usually considered as one of the key components in various applications. To maintain the availability of induction motors, it calls for a reliable condition monitoring and prognostics strategy. Among the common induction motor faults, stator winding faults are usually diagnosed with current and voltage signals. However, if the same performance can be achieved, the use of vibration signal is favorable because the winding fault diagnostic method can be integrated with bearing fault diagnostic method which has been successfully proven with vibration signal. Existing work concerning vibration for winding faults often takes it either as auxiliary to magnetic flux, or is not able to detect the winding faults unless severity is already quite significant. This paper proposes a winding fault diagnostic method based on vibration signals measured on the mechanical structure of an induction motor. In order to identify the signature of faults, time synchronous averaging was firstly applied on the raw vibration signals to remove discrete frequency components originating from the dynamics of the shaft and/or gears, and the spectral kurtosis filtering was subsequently applied on the residual signal to emphasize the impulsiveness. For the purpose of enhancing the residual signal in practice, a demodulation technique was implemented with the help of kurtogram. A series of experiments have been conducted on a three-phase induction motor test bed, where stator inter-turn faults can be easily simulated at different loads, speeds and severity levels. The experimental results show that the proposed method was able to detect inter-turn faults in the induction motor, even when the fault is incipient.
 
 

Studying the Performances of Induction Motor Used in Electric Car

This research includes study of the performances of induction motor used in the electric car, as well as performances of an electronic inverter based on Field Oriented control used to drive this induction motor.The running equations of IM and Controller in dynamic state with reference frame d – q were considered. These equations were modelled into computer form based using Matlab Simpower facilities obtaining a complete model. 3-Phase IM is considered and its parameters were used for simulation, in order to be mounted in certain car that is manufactured in Syria, and transform it to electric car.Also, it includes a study of electronic inverter appropriate to drive such motor and control its speed. It operates based on vector control technology.The study of the motor performances was conducted within presumptions of changing car load from one passenger (the driver) to five passengers and having different resistant torques.The tests of induction motor used in the electric car simulate running of the car having one passenger when car is stopped; simulate running of electric car starting IM from 0 speed and accelerating till a steady speed is reached, keeping this steady speed for a period of time, then reduce speed till car is stopped and finely Simulate running of electric car on rural roads having some holes and small slopes which cause several small acceleration and sudden breaks.Some conclusions and remarks about performances and behaviour of IM were concluded.

Classification of Induction Machine Faults using Time Frequency Representation and Particle Swarm Optimization

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

Statistical and Neural-Network Approaches for the Classification of Induction Machine Faults Using the Ambiguity Plane Representation

A novel hybrid feature-reduction methodology is proposed as a contribution to the induction motor fault classification, to improve the classification rate of the current waveform events related to varieties of induction machine faults. This methodology relies on the combination of a feature-extraction technique based on the smoothed ambiguity plane designed for maximizing the separability between classes using Fisher's discriminant ratio, with the feature-selection technique, based on the proposed error-probability model to select an optimal number of the extracted features. This model depends on two parameters, namely, the smoothing kernel used to derive the features and the distance measurement. The proposed methodology is validated experimentally on a 5.5-kW induction motor test bench, and their performances are compared with the classification algorithm based on neural networks with sigmoid and wavelets in hidden neurons, known as a flexible tool for learning and recognizing system faults. The results obtained show an accurate classification independent from the load level.

Transducer Development for Nonintrusive Load Monitoring of Rotating Machinery


 
 
 Monitoring machine runtime health parameters through nonintrusive means can greatly reduce the up-front time and resource barriers to entry of adding instrumentation to existing plant infrastructure. This work presents the design and evaluation of three transducers as part of a nonintrusive load monitoring system for rotating machinery. Data collected using a custom designed, small-scale induction motor test stand shows the dependence of a large air core RF coil, small RF coil array, and Hall effect sensor outputs on applied motor speeds and mechanical loads (estimated based on generator power). Analysis indicates that the large air core RF coil transducer and the presented method for using nonintrusive collection of induction motor speed and stray flux can statistically measure the difference between any two load points with 95% confidence, if their values differ by 6.6% full scale or greater (±2). Additionally, areas of further research toward generalization of the approach are identified.
 
 

Experimental Tests of Dual Three-Phase Induction Motor Under Faulty Operating Condition

This paper describes a set of experimental tests on a dual three-phase induction machine for fault-tolerant applications. Both three-phase and six-phase machine operations are considered. Different winding configurations are investigated and compared in case of both open-circuit and short-circuit faults. Experimental tests for each configuration are reported at no-load and under load operating conditions.

Nonlinear time-harmonic finite-element analysis of coupled circuits and fields in low frequency electromagnetic devices

Many electromagnetic devices operate under sinusoidal excitation, in which case a time-harmonic (TH) analysis may be applied; in particular, a TH field solution is much more economic than a time-transient field solution. Although the material nonlinearity cannot be strictly taken into account in the TH case, it determines the true operating condition of the device, together with the external circuit connections. In this paper, an efficient finite-element (FE) formulation to solve the 2D TH circuit-field (CF) problem posed by low-frequency (LF) electromagnetic devices is presented, approximately taking into account the effect of the material nonlinearity. Consideration is given to theoretical aspects that had not been previously studied: the resulting nonlinear complex equation does not possess an exact Jacobian, because one of its terms involves a nonanalytic function. This is circumvented by using pseudo-Jacobians derived from the Cauchy–Riemann expressions. Solid and filamentary conductors may be connected to external circuits of arbitrary topology using a novel Modified Nodal Analysis (MNA) approach. Methods for correcting magnetization curves and calculating the electromagnetic force are proposed. An induction motor test case is used to illustrate the capabilities of the formulation, and the numerical results are compared with those of a validated commercial package.

Comparison of IEEE 112 and New IEC Standard 60034-2-1

This paper describes a comparative study of induction motor testing standards IEEE 112 and newly published IEC 60034-2-1, primarily used in the United States and Europe, respectively. IEC 60034-2-1 has been refined from its earlier version IEC 60034-2 with reference to the IEEE 112. Six induction motors are tested following the two standards and the results are compared with regard to their instrumental accuracy and testing procedures. Power loss results are validated by the calorimetric method. A quantitative method is devised to evaluate the measurement uncertainty that can be interpreted into an efficiency deviation by quadrature addition. This paper is aimed to provide a guideline on interpreting the measured machine efficiency values using these standards and to validate the new IEC standard.

Accurate diagnosis of induction machine faults using optimal time–frequency representations

This paper presents a new diagnosis method of induction motor faults based on time–frequency classification of the current waveforms. This method is composed of two sequential processes: a feature extraction and a rule decision. In the process of feature extraction, the time–frequency representation (TFR) has been designed for maximizing the separability between classes representing different faults. The diagnosis is realised in two levels; the first one allows the detection of different faults—bearing fault, stator fault and rotor fault. The second one refines this detection by the determination of severity degree of faults, which are already identified on the previous level. The diagnosis is independent of the level of load. This method is validated on a 5.5 kW induction motor test bench.

Coupling Circuit Systems and Finite Element Models: A 2-D Time-Harmonic Modified Nodal Analysis Framework

A new, systematic way of coupling low-frequency finite-element (FE) models with circuit systems is proposed using a modified nodal analysis framework. Solid and filamentary conductors can be equally treated as magnetic vector potential-controlled voltage sources. Their matrix contributions to the coupled system are basically the same, leading to a natural way of adding conductors to arbitrary circuit topologies. Algebraic equations of the same type describe the coupling between FE and circuit models, for both massive and filamentary conductors. Any class of independent and dependent source can be considered as well as resistances, inductances, capacitances, transformers, auto-transformers and magnetically-coupled branches. The resulting matrix for the coupled problem is symmetric if the circuit configuration does not contain voltage- or current-controlled sources. The methodology is developed for the general nonlinear time-harmonic problem, but it can be extended to the transient case. An induction motor test case is employed to show the power of the new coupling approach. Comparison of the results against a well-known, validated commercial software (Flux2D) shows that the code developed in this work performs efficiently.

Classification of Induction Machine Faults by Optimal Time–Frequency Representations

This paper presents a new diagnosis method of induction motor faults based on time-frequency classification of the current waveforms. This method is based on a representation space, a selection criterion, and a decision criterion. In order to define the representation space, an optimized time-frequency representation (TFR) is designed from the time-frequency ambiguity plane. The selection criterion is based on Fisher's discriminant ratio, which allows one to maximize the separability between classes representing different faults. A distinct TFR is designed for each class. The following two classifiers were used for decision criteria: the Mahalanobis distance and the hidden Markov model. The flexibility of this method allows an accurate classification independent from the level of load. This method is validated on a 5.5-kW induction motor test bench.

Experimental Study on Induction Motor With Superconducting Secondary Conductors

The authors have studied a superconducting induction motor with Bi-2223/Ag HTS secondary conductors in the rotor. If the superconductor is applied to an induction motor, a higher efficiency and a higher power and a higher starting torque can be expected. The authors remodelled the rotor of a commercial 200 W (4 pole) induction motor and made an experimental HTS induction motor. The cast aluminum in the rotor slots were cut-in by 5 mm in depth and HTS tapes were put in the slots. Thus, the original conventional 200 W induction motor was remodeled to a HTS induction motor. The experimental motor was immersed in a liquid nitrogen bath. And, a no-load test, a locked test, a variable frequency locked test, and a load test of the HTS induction motor were carried out in liquid nitrogen bath. The experimental results are presented together with some theoretical analysis.

Induction Motor Tests Using MATLAB/Simulink and Their Integration Into Undergraduate Electric Machinery Courses

This work describes MATLAB/Simulink implementation of three induction motor tests, namely dc, no-load, and blocked-rotor tests performed to identify equivalent circuit parameters. These simulation models are developed to support and enhance electric machinery education at the undergraduate level. The proposed tests have been successfully integrated into electric machinery courses at Drexel University, Philadelphia, PA, and Nigde University, Nigde, Turkey.

Modern online testing of induction motors for predictive maintenance and monitoring

Online testing of motors, diagnostics, and motor monitoring have shown large scientific development in the past few years, outgrowing the stage of RMS current and voltage measurements. This stems from current and voltage signature analysis which has progressed from the laboratory and the work of dedicated specialist experts to become the base for modern instrumentation available to plant operatives. In addition to line-fed motors, a clear view of variable-frequency drive applications is now possible without requiring connection directly to the motor terminals. The use of the motor itself as a transparent sensor, making shaft torque signatures available at the motor control cabinet, allows for advanced diagnostics of the voltage supply, motor, and load system.