Showing papers on "Induction motor published in 2014"
TL;DR: Comparisons with other conventional methods, such as principal component analysis, local preserving projection, canonical correction analysis, maximum margin criterion, LDA, and marginal Fisher analysis, show the superiority of TR-LDA in fault diagnosis.
Abstract: Bearings are critical components in induction motors and brushless direct current motors. Bearing failure is the most common failure mode in these motors. By implementing health monitoring and fault diagnosis of bearings, unscheduled maintenance and economic losses caused by bearing failures can be avoided. This paper introduces trace ratio linear discriminant analysis (TR-LDA) to deal with high-dimensional non-Gaussian fault data for dimension reduction and fault classification. Motor bearing data with single-point faults and generalized-roughness faults are used to validate the effectiveness of the proposed method for fault diagnosis. Comparisons with other conventional methods, such as principal component analysis, local preserving projection, canonical correction analysis, maximum margin criterion, LDA, and marginal Fisher analysis, show the superiority of TR-LDA in fault diagnosis.
354 citations
Patent•
24 Apr 2014
TL;DR: In this paper, a voltage is applied to the electric motor and actively controlled during operation of the motor during the operation of an electric motor to cause the motor to turn at a desired speed.
Abstract: A method for controlling an electric motor. A desired speed is identified for the electric motor during operation of the electric motor. A voltage is identified to cause the electric motor to turn at the desired speed. The voltage is applied to the electric motor and actively controlled during operation of the electric motor.
327 citations
TL;DR: An improved MPTC with duty cycle control is proposed by optimizing the vector selection and its duration simultaneously when minimizing both torque and flux errors, and better steady-state performance at both low and high speeds is achieved, even if the sampling frequency is reduced by half.
Abstract: Model predictive torque control (MPTC) is emerging as a powerful control scheme for high performance control of induction motor (IM) drives. Compared to direct torque control, MPTC is more effective and accurate in voltage vector selection by incorporating the system model directly with the finite switching states. However, for two-level inverter-fed IM drives, the sampling frequency of MPTC has to be high to achieve good performance due to the limited number of voltage vectors. Recently, the concept of duty cycle control was introduced in MPTC by inserting a null vector along with the selected active voltage vector to achieve torque ripple reduction. The active vector is first selected from conventional MPTC and then its duration is determined based on a certain principle. The cascaded processing of active vector and its duration leads to poor low-speed performance and the sampling frequency still has to be high. This paper proposes an improved MPTC with duty cycle control by optimizing the vector selection and its duration simultaneously when minimizing both torque and flux errors. As a result, better steady-state performance at both low and high speeds is achieved, even if the sampling frequency is reduced by half. The effectiveness of the proposed MPTC is verified by both simulation and experimental results.
304 citations
TL;DR: In this article, an attempt is made to provide a physically meaningful insight into current control of a six-phase induction machine, by showing that the fictitious x-y currents can be physically interpreted as the circulating currents between the two three-phase windings.
Abstract: Using the vector space decomposition approach, the currents in a multiphase machine with distributed winding can be decoupled into the flux and torque producing α-β components, and the loss-producing x-y and zero-sequence components. While the control of α-β currents is crucial for flux and torque regulation, control of x-y currents is important for machine/converter asymmetry and dead-time effect compensation. In this paper, an attempt is made to provide a physically meaningful insight into current control of a six-phase machine, by showing that the fictitious x-y currents can be physically interpreted as the circulating currents between the two three-phase windings. Using this interpretation, the characteristics of x-y currents due to the machine/converter asymmetry can be analyzed. The use of different types of x-y current controllers for asymmetry compensation and suppression of dead-time-induced harmonics is then discussed. Experimental results are provided throughout the paper, to underpin the theoretical considerations, using tests on a prototype asymmetrical six-phase induction machine.
239 citations
TL;DR: This paper presents an investigation of the finite-control-set model predictive control (FCS-MPC) of a five-phase induction motor drive, and guidelines for the best switching state set and weighting factor selections are established.
Abstract: This paper presents an investigation of the finite-control-set model predictive control (FCS-MPC) of a five-phase induction motor drive. Specifically, performance with regard to different selections of inverter switching states is investigated. The motor is operated under rotor flux orientation, and both flux/torque producing (d-q) and nonflux/torque producing (x-y) currents are included into the quadratic cost function. The performance is evaluated on the basis of the primary plane, secondary plane, and phase (average) current ripples, across the full inverter's linear operating region under constant flux-torque operation. A secondary plane current ripple weighting factor is added in the cost function, and its impact on all the studied schemes is evaluated. Guidelines for the best switching state set and weighting factor selections are thus established. All the considerations are accompanied with both simulation and experimental results, which are further compared with the steady-state and transient performance of a proportional-integral pulsewidth modulation (PI-PWM)-based current control scheme. While a better transient performance is obtained with FCS-MPC, steady-state performance is always superior with PI-PWM control. It is argued that this is inevitable in multiphase drives in general, due to the existence of nonflux/torque producing current components.
238 citations
TL;DR: In this article, Mihajlovic et al. investigated the effect of hidden oscillations in a two-mass mathematical model of a drilling system and showed that these effects may lead to drill string failures and breakdowns.
Abstract: This work is devoted to the investigation of mathematical models of drilling systems described by ordinary differential equations. Here, we continue the study done by the researchers from Eindhoven where the two-mass mathematical model of a drilling system has been investigated (Mihajlovic et al. J. Dyn. Syst. Meas. Control 126(4): 709–720, 2004; de Bruin et al. Automatica 45(2): 405–415, 2009). The modified version of this model, which takes into account a full description of an induction motor, is studied. It is shown that such complex effects as hidden oscillations may appear in these kinds of systems. These effects may lead to drill string failures and breakdowns.
233 citations
TL;DR: This paper proposes a fault-tolerant speed control for five-phase induction motor drives with the ability to run the system before and after an open-phase fault condition using an FCS-MPC strategy.
Abstract: Fault tolerance is one of the most interesting features in stand-alone electric propulsion systems. Multiphase induction motor drives are presented like a better alternative to their three-phase counterparts because of their capability to withstand faulty situations, ensuring the postfault operation of the drive. Finite-control set model-based predictive control (FCS-MPC) has been introduced in the last decade like an interesting alternative to conventional controllers for the electrical torque and current regulation of multiphase drives. However, FCS-MPC strategies for multiphase drives with the ability to manage pre- and postfault operations have not been addressed at all. This paper proposes a fault-tolerant speed control for five-phase induction motor drives with the ability to run the system before and after an open-phase fault condition using an FCS-MPC strategy. Experimental results are provided in order to validate the functionality of the proposed control method, maintaining rated currents and ensuring fast and ripple-free torque response.
229 citations
TL;DR: A speed estimation scheme based on second-order sliding-mode supertwisting algorithm (STA) and model reference adaptive system (MRAS) estimation theory, in which both variations of stator resistance and rotor resistance are deliberately treated, alleviating the chattering behavior without increasing the complexity.
Abstract: Parameter identification plays an important role in speed estimation schemes. This paper presents a speed estimation scheme based on second-order sliding-mode supertwisting algorithm (STA) and model reference adaptive system (MRAS) estimation theory, in which both variations of stator resistance and rotor resistance are deliberately treated. A stator current observer is designed based on the STA, which is utilized to take the place of the reference voltage model of the standard MRAS algorithm. The observer is insensitive to the variation of rotor resistance and perturbation when the states arrive at the sliding mode. Derivatives of rotor flux are obtained and designed as the state of MRAS, thus eliminating the integration. Furthermore, in order to improve the near-zero speed operation, a parallel adaptive identification of stator resistance is designed relying on derivatives of rotor flux and stator current. Compared with the first-order sliding-mode speed estimator, the proposed scheme makes full use of the auxiliary sliding-mode surface, thus alleviating the chattering behavior without increasing the complexity. The robustness and effectiveness of the proposed scheme have been validated experimentally.
220 citations
TL;DR: In this paper, a technique based on a recent enhancement on wavelets known as complex wavelets is proposed for identifying multiple faults in vector controlled induction motor drives (VCIMDs).
Abstract: Embedded variable frequency induction motor drives are now an integral part of any industry due to their improved speed regulation and fast dynamic response. Hence, their diagnosis becomes vital to avoid downtimes and economic losses. In this paper, a technique based on a recent enhancement on wavelets, known as complex wavelets, is proposed for identifying multiple faults in vector controlled induction motor drives (VCIMDs). Radial, axial, and tangential vibrations are analyzed for diagnostic purpose. Initially, a relatively simple thresholding based method is investigated for feasibility of diagnosis under variable frequency and load conditions. In the second part, the feature extraction and classifier modeling are discussed, in which the nearly shift-invariant complex wavelet based model is compared with the discrete wavelet transform (DWT) for its applicability in detecting multiple faults. The fault conditions considered here are the most prominent ones such as interturn fault, interturn fault under progression, and bearing damage. Comparable performances of support vector machine (SVM) based models and simple technique based on k-nearest neighbor (k-NN) show the importance of efficient representation of input space by analytical wavelet based feature extraction. The performance indexes show the applicability of the scheme for industrial drives under variable frequencies and load conditions.
202 citations
TL;DR: Simulation and experimental results are presented to show the effectiveness and the merits of the proposed approach that offers the possibility to detect stator fault and to discriminate it from other abnormality conditions responsible for the same motor behavior by comparing the signature analyses of the two considered quantities.
Abstract: In this paper, the instantaneous active and reactive power signature analyses are presented for stator fault diagnosis in operating squirrel cage three-phase induction motors either directly connected to the mains or fed from inverters. Both simulation and experimental results are presented to show the effectiveness and the merits of the proposed approach that offers the possibility to detect this type of fault and to discriminate it from other abnormality conditions responsible for the same motor behavior by comparing the signature analyses of the two considered quantities.
177 citations
TL;DR: This paper presents a multiphysics modeling of a switched reluctance motor (SRM) to simulate the acoustic radiation of the electrical machine using a 2-D finite-element model of the motor to simulate its magnetic properties and aMultiphysics mechatronic model ofThe motor and controls to simulate operating conditions.
Abstract: This paper presents a multiphysics modeling of a switched reluctance motor (SRM) to simulate the acoustic radiation of the electrical machine. The proposed method uses a 2-D finite-element model of the motor to simulate its magnetic properties and a multiphysics mechatronic model of the motor and controls to simulate operating conditions. Magnetic forces on the stator are calculated using finite-element analysis and are used as the excitation on a forced response analysis that contains a finite-element model of the motor stator structure. Finally, sound power levels are calculated using the boundary element method. Simulation results of the model are shown and compared with experimental measurements for a four-phase 8/6 SRM.
TL;DR: Simulated and experimental results show that the proposed adaptive robust position control scheme provide high-performance dynamic characteristics, and that it is robust with respect to plant parameter variations and external load disturbances.
Abstract: An adaptive robust position control for real-time high-performance applications of induction motors is developed in this work. The proposed sliding-mode controller provides a global asymptotic position tracking in the presence of model uncertainties and load torque variations. The proposed control scheme incorporates an adaptation law for the switching gain, so that the controller can calculate the switching gain value that is necessary to overcome the existing system uncertainties. The design also incorporates a sliding-mode-based load torque and rotor flux observers in order to improve the control performance without using sensors that increase cost and reduce reliability. The proposed design does not present a high computational cost and, therefore, can be easily implemented in real-time applications. Simulated and experimental results show that this scheme provide high-performance dynamic characteristics, and that it is robust with respect to plant parameter variations and external load disturbances.
TL;DR: In this article, the Hilbert-Huang transform of vibration data and power spectral density of current and acoustic signals are used as the features in a hierarchical classifier to distinguish a faulty motor from a healthy motor.
Abstract: This paper presents a stand-alone multisensor wireless system for continuous condition monitoring of induction motors. The proposed wireless system provides a low-cost alternative to expensive condition monitoring technology available through dedicated current signature analysis or vibration monitoring equipment. The system employs multiple sensors (acoustic, vibration, and current) mounted on a common wireless platform. The faults of interest are static and dynamic air-gap eccentricity, bearing damage, and their combinations. The Hilbert-Huang transform of vibration data and power spectral density of current and acoustic signals are used as the features in a hierarchical classifier. The proposed wireless system can distinguish a faulty motor from a healthy motor with a probability of 99.9% of correct detection and less than 0.1% likelihood of false alarm. It can also discriminate between different fault categories and severity with an average accuracy of 95%.
TL;DR: It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates.
Abstract: This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. Experimental findings, carried out on a closed-loop system consisting of a low-power induction-motor-load system, a proportional-integral-type controller, and the proposed estimator, are shown with the aim of verifying the goodness of the whole closed-loop control system.
TL;DR: A sensorless control scheme is presented for induction motors with core loss, designed using a high order sliding mode twisting algorithm, to track a desired rotor velocity signal and an optimal rotor flux modulus, minimizing the power loss in copper and core.
Abstract: In this paper, a sensorless control scheme is presented for induction motors with core loss. First, a controller is designed using a high order sliding mode twisting algorithm, to track a desired rotor velocity signal and an optimal rotor flux modulus, minimizing the power loss in copper and core. Then, a super-twisting (ST) sliding mode observer for stator current is designed and the rotor flux is calculated, by means of the equivalent control method. Two methods for the rotor velocity estimation are then proposed. The first consists of a further super-twisting sliding mode observer for rotor fluxes, with the purpose of retrieving the back-electromotive force components by means of the equivalent control method. These components are functions of the rotor velocity which, hence, can be easily determined. The second method is based on a generalization of the phase-locked loop methodology. Finally, a simple Luenberger observer is designed, filtering the rotor velocity estimate and giving also an estimate of the load torque. The performance of the motor is verified by means of numeric simulations and experimental tests, where good tracking results are obtained.
TL;DR: A simple method for single switch and double switches open-circuit fault diagnosis in pulsewidth-modulated voltage-source inverters (PWM VSIs) for vector-controlled induction motor drives and the results show the effectiveness of the proposed method.
Abstract: This paper proposes a simple method for single switch and double switches open-circuit fault diagnosis in pulsewidth-modulated voltage-source inverters (PWM VSIs) for vector-controlled induction motor drives, which also applies to secondary open-circuit fault diagnosis. According to the phase angle of one phase current, the repetitive operation process of VSI is evenly divided into six operating stages by certain rules. At each stage, only three of the six power switches exert a vital influence on this operation and the others make a negligible influence. An open-circuit fault of power switches introduces the repetitive current distortions, whose period is identical to that of the three-phase currents. The current distortions appear at faulty stages and disappear at healthy stages. The stage is determined by recalculating the current vector rotating angle. The d - and q-axis current repetitive distortions are applied to the detection of faulty switches due to its simplicity and fair robustness, while the faulty stages are used for the identification of faulty switches. The simulations and experiments are carried out and the results show the effectiveness of the proposed method.
TL;DR: A filtering process is proposed that uses advanced notch filters in order to remove constant frequency components present in the current of an induction motor, prior to the computation of its distribution, to study rotor asymmetries and mixed eccentricities in transient operation of machines directly connected to the grid.
Abstract: During the last years, several time-frequency decomposition tools have been applied for the diagnosis of induction motors, for those cases in which the traditional procedures, such as motor current signature analysis, cannot yield the necessary response. Among them, the Cohen distributions have been widely selected to study transient and even stationary operation due to their high-resolution and detailed information provided at all frequencies. Their main drawback, the cross-terms, has been tackled either modifying the distribution, or carrying out a pretreatment of the signal before computing its time-frequency decomposition. In this paper, a filtering process is proposed that uses advanced notch filters in order to remove constant frequency components present in the current of an induction motor, prior to the computation of its distribution, to study rotor asymmetries and mixed eccentricities. In transient operation of machines directly connected to the grid, this procedure effectively eliminates most of the artifacts that have prevented the use of these tools, allowing a wideband analysis and the definition of a precise quantification parameter able to follow the evolution of their state.
TL;DR: An ensemble of hybrid intelligent models that is useful for condition monitoring of induction motors that consists of the Fuzzy Min–Max (FMM) neural network and the Random Forest model comprising an ensemble of Classification and Regression Trees is proposed.
Abstract: In this paper, a review on condition monitoring of induction motors is first presented Then, an ensemble of hybrid intelligent models that is useful for condition monitoring of induction motors is proposed The review covers two parts, ie, (i) a total of nine commonly used condition monitoring methods of induction motors; and (ii) intelligent learning models for condition monitoring of induction motors subject to single and multiple input signals Based on the review findings, the Motor Current Signature Analysis (MCSA) method is selected for this study owing to its online, non-invasive properties and its requirement of only single input source; therefore leading to a cost-effective condition monitoring method A hybrid intelligent model that consists of the Fuzzy Min–Max (FMM) neural network and the Random Forest (RF) model comprising an ensemble of Classification and Regression Trees is developed The majority voting scheme is used to combine the predictions produced by the resulting FMM–RF ensemble (or FMM–RFE) members A benchmark problem is first deployed to evaluate the usefulness of the FMM–RFE model Then, the model is applied to condition monitoring of induction motors using a set of real data samples Specifically, the stator current signals of induction motors are obtained using the MCSA method The signals are processed to produce a set of harmonic-based features for classification using the FMM–RFE model The experimental results show good performances in both noise-free and noisy environments More importantly, a set of explanatory rules in the form of a decision tree can be extracted from the FMM–RFE model to justify its predictions The outcomes ascertain the effectiveness of the proposed FMM–RFE model in undertaking condition monitoring tasks, especially for induction motors, under different environments
TL;DR: In this article, a tristate pulse-width modulation technique has been employed, in which three adjacent switching states are used to construct the reference voltage, and the active switching states were arranged at the edge and the center of a PWM cycle.
Abstract: Three-phase current reconstruction technique using dc current information in conventional two-level inverters can be used for the purpose of cost reduction and sensor fault tolerance. A novel phase current reconstruction scheme, with reduced immeasurable area and common mode voltage, is proposed in this paper. A tristate pulse-width modulation technique has been employed, in which three adjacent switching states are used to construct the reference voltage. The active switching states are arranged at the edge and the center of a PWM cycle. Fixed sampling and simultaneous three-phase currents can be easily achieved with very little hardware and software requirements. A detailed analysis of the effects of nonidealities leads to regional modifications of the switching sequence resulting in almost the whole hexagon as the feasible area. The usefulness of the proposed reconstruction algorithm has been verified by experimental results obtained from a 4-kW induction motor drive system. Smooth transitions between the redundant and fault-tolerant modes were observed.
TL;DR: Two active fault-tolerant control schemes dedicated to induction-motor drives in electric or hybrid vehicle powertrains are presented and compared and a comparative study is carried out between the two FTC schemes.
Abstract: In this paper, two active fault-tolerant control (AFTC) schemes dedicated to induction-motor drives in electric or hybrid vehicle powertrains are presented and compared. Fault detection and mitigation are merged to propose a robust algorithm against speed-sensor faults (fault is modeled as significant additional noise or an exponential type emulating a bias) leading to uncertainties in the measurement. The first architecture is a hybrid fault tolerant-control (FTC) with proportional-integral and H∞ controllers; the second architecture is the generalized internal model control (GIMC) with a natural reconfiguration. Both are built to ensure resilience while keeping good dynamic performances. For each architecture, the speed-sensor fault detection is based on an extended Kalman filter (EKF) that generates a residual vector. The correction method is calculated differently for the two schemes specifically in the switching transition phase between the nominal and robust controllers. A comparative study is carried out between the two FTC schemes.
TL;DR: Four basic types of synchronized discontinuous PWM sequences that ensure synchronization, three-phase symmetry, and half-wave symmetry are presented that are compared with that of the conventional synchronized space vector PWM.
Abstract: The high-power voltage source inverters are switched at low frequency to reduce the losses in the inverter. The discontinuous pulsewidth-modulation (PWM) sequences reduce the switching frequency to two-thirds compared to the conventional continuous PWM sequences. At low switching frequency, the output will be rich in harmonics, and synchronization is a must to avoid subharmonics. This paper presents four basic types of synchronized discontinuous PWM (DPWM) sequences that ensure synchronization, three-phase symmetry, and half-wave symmetry. The proposed synchronized DPWM sequences are verified through simulation and experiment on a constant- v/f open-loop induction motor drive. The performance of the proposed DPWM algorithms is studied in the entire modulation region, including the overmodulation region, and is compared with that of the conventional synchronized space vector PWM. A different type of DPWM with low common-mode voltage is suggested for low-modulation region and verified experimentally.
21 Sep 2014
TL;DR: SRM is the most appropriate motor for EV because the weight of SRM is low, its reliability is high, it operates fault-tolerance and according to the acceleration time, its performance is better than IM and BLDC.
Abstract: In this study, Switched Reluctance Motor (SRM), Induction Motor (IM), Brushless DC Motor, and Permanent Magnet Motor (PM), and their drives have been compared with the efficiency, cost, weight, cooling, maximum speed, reliability, fault tolerance, power ratings, and vehicle acceleration time. Hence, a comprehensive literature research on motor types and their drives used in EV has been made. According to these researches, some conclusions have been obtained. It has been seen that PM BLDC motors and their drives are the most efficient and have high power density, brushless DC motors and their drives have low cost, IM is appropriate for controllability and cost, the weight of SRM is low, its reliability is high, it operates fault-tolerance and according to the acceleration time, its performance is better than IM and BLDC. Hence, SRM is the most appropriate motor for EV.
TL;DR: In this paper, the authors provide a substantial updated review of the state-of-the-art in direct torque control (DTC) IM control algorithms and their applications to minimize the energy losses and improve the system efficacy.
Abstract: For a reliable dynamic system and significant amount of savings in energy usage, adjustable speed drives (ASD) can play a vital role. The proper control of motor drives can give a good system response and also increase the efficacy of the drive. Recently the direct torque control (DTC) strategy has drawn great attention for motor drives due to its simplicity, insensitivity to the motor parameters, high reliability and improved dynamic response. Many control strategies have been developed for the improvement of conventional DTC drives focusing specifically on torque and flux. A number of techniques have been formulated and successfully implemented for induction motor (IM) control. This paper aims to provide a substantial updated review, albeit by no means complete, for those who are interested in keeping track of the present state-of-the-art in this field and working further. The review focuses on different control algorithms of DTC IM drives and their applications to minimize the energy losses and improve the system efficacy.
TL;DR: In this article, a brief review of direct torque control (DTC) of induction motors and its implementation for electric vehicle (EV) applications is presented, taking into consideration the vehicle mechanics and aerodynamics of electric vehicles.
Abstract: The first and the most important step in solving the environmental problems created by cars with internal combustion engines is research and development of electric vehicles. Selection of a proper drive and optimal control strategy of electric vehicles are the major factors to obtain optimal energy management in order to extend the running distance per battery charge. This paper presents a brief review of direct torque control (DTC) of induction motors (IM) as well as its implementation for electric vehicle (EV) applications. First, the basic DTC technique based on hysteresis controllers will be introduced, and then an overview of the major problems in a basic DTC scheme will be presented and explained, as well as some efforts for improving the technique. The main section presents a critical review of DTC for EV applications, taking into consideration the vehicle mechanics and aerodynamics of electric vehicles. The review is very important to provide guidelines and insights for future research and development on the DTC of IM drives for sustainable reliability and energy efficient EV applications.
TL;DR: A simple and robust method for parameter estimation at rotor standstill is presented for interior permanent magnet (IPM) synchronous machines and the validity of the suggested method has been verified by implementation on two IPM motor prototypes.
Abstract: In this paper, a simple and robust method for parameter estimation at rotor standstill is presented for interior permanent magnet (IPM) synchronous machines. The estimated parameters are the stator resistance through dc test, the dq inductances using high-frequency injection, and the permanent magnet flux by means of a closed-loop speed control maintaining rotor stationary. The proposed method does not require either locking the rotor or additional/special power supplies. The validity of the suggested method has been verified by implementation on two IPM motor prototypes. Finally, the estimated parameters have been compared against results obtained through finite-element simulations and with machine magnetic characterization, separately performed, to validate the method's effectiveness. Saturation and cross-saturation effects are taken care of through amplitude modulation and cross-axis current application, respectively.
TL;DR: In this paper, a 2D wavelet scalogram has been used for the detection and occurrence of outer race faults of various sizes in ball bearings of mechanical systems using motor current signatures of induction motor.
TL;DR: In this paper, behavioral models based on Thevenin equivalents are proposed for a dc-fed three-phase motor drive system to accurately predict the total EMI noise in accordance with the DO-160 standards for aerospace applications.
Abstract: Behavioral electromagnetic interference (EMI) models based on Thevenin equivalents are proposed for a dc-fed three-phase motor drive system. Both common-mode (CM) and differential-mode (DM) noise models are developed to accurately predict the total EMI noise in accordance with the DO-160 standards for aerospace applications. Beyond the switching frequency of the drive, the CM noise model is found to behave like a two-port linear network and is shown to predict changes in the input-side EMI due to any changes in the load-side parameters or vice versa. Simplified one-port behavioral models for DM noise are then used to predict the total noise at both input and output side of the motor drive. Such models can be very useful in system level EMI analysis and also in understanding how EMI filters and harnesses affect the overall EMI in a motor drive system. The models run in the frequency domain and are validated with experiments up to 30 MHz.
TL;DR: In this article, a methodology based on thermographic image segmentation for fault detection in induction motors, and the repercussion of these faults along the kinematic chain is presented.
TL;DR: In this paper, the authors used correlation and wavelet-based analysis for extracting necessary features from the recorded data and used the features obtained from same types of motors with different kind of faults for the classification using the Self-Organizing Maps method.
TL;DR: In this paper, a wavelet-based detection method is proposed and verified on custom-built lab motors and 6.6kV motors misdiagnosed with broken bars via steady-state spectrum analysis.
Abstract: Axial cooling air ducts in the rotor of large induction motors are known to produce magnetic asymmetry and can cause steady-state current or vibration spectrum analysis based fault detection techniques to fail. If the number of axial air ducts and that of poles are identical, frequency components that overlap with that of rotor faults can be produced for healthy motors. False positive rotor fault indication due to axial ducts is a common problem in the field that results in unnecessary maintenance cost. However, there is currently no known test method available for distinguishing rotor faults and false indications due to axial ducts other than offline rotor inspection or testing. Considering that there is no magnetic asymmetry under high slip conditions due to limited flux penetration into the rotor yoke, the detection of broken bars under the start-up transient is investigated in this paper. A wavelet-based detection method is proposed and verified on custom-built lab motors and 6.6-kV motors misdiagnosed with broken bars via steady-state spectrum analysis. It is shown that the proposed method provides the reliable detection of broken bars under the start-up transient independent of axial duct influence.