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1
Content available remote Induction motor stator faults identification using modified MRAS type estimator
EN
In the paper, the possibility of the MRAS (Model Reference Adaptive System) estimator application to estimate the stator resistance of an induction motor during stator short-circuits is presented. To increase the accuracy of the motor parameter reconstruction, a modified induction motor model was used, taking into account the possibility of simulating short circuits to develop a resistance estimator. The tests were performed in the DTC-SVM vector control system. The simulation results made in Matlab Simulink environment are presented under different drive conditions.
PL
W artykule przedstawiono możliwość wykorzystania estymatora typu MRAS (Model Reference Adaptive System) do estymacji rezystancji stojana silnika indukcyjnego podczas zwarć zwojowych. W celu zwiększenia dokładności odtwarzania parametru silnika estymator opracowano w oparciu o zmodyfikowany model maszyny, uwzględniający możliwość symulowania zwarć. Badania wykonano w układzie sterowania wektorowego DTC-SVM. Przedstawiono wyniki symulacyjne wykonane w środowisku Matlab Simulink.
EN
This article presents a new development of an indirect stator flux-oriented controller for sensorless speed induction motor drive utilising instantaneous and steady-state values, respectively, of a fictitious resistance symbolised as R_f. The dimension of the fictitious quantity, in this context, is the ohm, which is the difference between the stator d- and q-axis fictitious resistances. However, from the measurement of the stator voltage and currents of the machine, two independent resistance estimators are built. Therefore, the first is considered as a reference model of the induction machine (IM), and the second is considered as an adjustable model. Subsequently, the error between the states of the two models is used to drive a suitable adaptation mechanism that generates the estimation of the speed, for the adjustable model. Furthermore, the structure of the proposed estimator is free from stator resistance and eliminates the requirement of any flux computation. All the detailed simulation study is carried out in MATLAB/Simulink to validate the proposed method and to highlight the robustness and the stability of the proposed model reference adaptive system estimator.
EN
The paper presents a novel model predictive flux control (MPFC) scheme for three-level inverter-fed sensorless induction motor drive operated in a wide speed region, including field weakening. The novelty of the proposed drive lies in combining in one system a number of new solutions providing important features, among which are: very high dynamics, constant switching frequency, no need to adjust weighting factors in the predictive cost function, adaptive speed and parameter (stator resistance, main inductance) estimation. The theoretical principles of the optimal switching sequence predictive stator flux control (OSS-MPFC) method used are also discussed. The method guarantees constant switching frequency operation of a three-level inverter. For speed estimation, a compensated model reference adaptive system (C-MRAS) was adopted while for IM parameters estimation a Q-MRAS was developed. Simulation and experimental results measured on a 50 kW drive that illustrates operation and performances of the system are presented. The proposed novel solution of a predictive controlled IM drive presents an attractive and complete algorithm/system which only requires the knowledge of nominal IM parameters for proper operation.
EN
A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive system (MRAS) scheme is used to estimate the speed and the rotor resistance simultaneously. However, the error between the reference and the adjustable models, which are developed in the stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimates of speed and the rotor resistance from the stator voltage and the machine current measurements. The stator flux components in the stationary reference frame are estimated through a pure integration of the back electro-motive force (EMF) of the machine. When the machine is operated at low speed, the pure integration of the back EMF introduces an error in flux estimation which affects the performance torque and speed control. To overcome this problem, pure integration is replaced with a programmable cascaded low-pass filter (PCLPF). The stability analysis method of the MRAS estimator is verified in order to show the robustness of the rotor resistance variations. Experimental results are presented to prove the effectiveness and validity of the proposed scheme of sensorless ISFOC induction motor drive.
PL
W artykule omówiono możliwość wykrywania uszkodzenia prętów klatki wirnika silnika indukcyjnego z zastosowaniem techniki opartej na identyfikacji parametrów schematu zastępczego maszyny. Metodyka ta bazuje na założeniu, że wybrane uszkodzenia mogą objawiać się zmianami parametrów silnika, a ich identyfikacja w czasie rzeczywistym i obserwowanie tych zmian pozwala na wczesną identyfikację uszkodzenia. W pracy wykorzystano fakt, że w przypadku pęknięcia prętów klatki wirnika symptomem uszkodzenia jest wzrost rezystancji schematu zastępczego wirnika. Do odtwarzania tego parametru zastosowano estymator adaptacyjny z modelem odniesienia (MRAS). Badania silnika indukcyjnego przeprowadzono w układzie bezpośredniego sterowania polowo zorientowanego (DFOC). W artykule przedstawiono wyniki badań symulacyjnych oraz eksperymentalnych.
EN
This paper deals with the broken rotor bars detection in squirrel-cage induction motor using parameter identification approach. This method is based on the assumption, that the chosen failures may result in motor parameters variations. Real-time identification and observation of parameters variation allows to incipient fault detection. Increase of the rotor resistance value may be a good fault symptom, in the case of rotor bar damage. In the paper, the rotor resistance estimator based on the model reference adaptive system (MRAS) is utilized. The induction motor is operating in the direct field-oriented control structure, under different conditions. In the paper simulation and experimental results are shown.
EN
The paper is concerned with detection of a stator and rotor winding faults in a squirrel-cage induction motor. The idea of the fault detection is based on a hypothesis that each of windings faults results in a sharp increase or decrease of internal parameters’ values of the machine, therefore it can be treated as a suitable fault symptom. Resistances of the stator and rotor windings seem to be adequate quantities due to their direct relationship with the machine windings. An observation and analysis of the parameters’ changes in a realtime domain enables to an incipient detection of the fault. It is evident that internal parameters of the machine can’t be measured directly during operation on the drive system thus the only way is an estimation by specialized algorithms. In the paper two estimators based on Model Reference Adaptive System (MRAS) were utilized to achieve this goal. Two simple algorithms for faults detection are proposed as well. Detailed description of fault detection systems is included in the paper. Proposed systems were tested on computer simulations performed by MATLAB/Simulink software. Then, experimental tests were carried out on the laboratory setup to confirm usefulness of proposed approaches.
PL
Artykuł skupia się na wykrywaniu wybranych uszkodzeń uzwojeń stojana i wirnika silnika indukcyjnego klatkowego. Idea detekcji opiera się na założeniu, że każde uszkodzenie uzwojeń powoduje gwałtowną zmianę wartości wewnętrznych parametrów maszyny, co może być uznane jako miarodajny symptom uszkodzenia. Najbardziej odpowiednimi parametrami wydają się być rezystancje stojana i wirnika ze względu na bezpośrednie powiązanie z uzwojeniami silnika. Obserwacja i analiza zmian wartości tych parametrów w czasie rzeczywistym umożliwia wykrycie uszkodzenia w jego wczesnym stadium. W trakcie pracy napędu nie ma możliwości pomiaru rezystancji uzwojeń, dlatego też jedynym sposobem na uzyskanie informacji o ich aktualnych wartościach jest estymacja z zastosowaniem wyspecjalizowanych algorytmów. W pracy do realizacji tego celu zastosowano układy adaptacyjne z modelem odniesienia (MRAS). Ponadto zaproponowano również dwa proste algorytmy detekcji uszkodzeń uzwojeń stojana i wirnika. W artykule przedstawiono przegląd literatury dotyczący wykrywania uszkodzeń silnika indukcyjnego z zastosowaniem estymatorów parametrów. Proponowane rozwiązanie zostało sprawdzone poprzez analizę symulacyjną przeprowadzoną w środowisku MATLAB/Simulink a także zweryfikowane na stanowisku eksperymentalnym.
EN
A speed-sensorless control of induction motor drive based MRAS-Neural Self-Tuning IP Observer is proposed. A Model Reference Adaptive Systems speed observer can give good rotor speed estimation, but speed errors will occur during low speed. In this work the rotor speed is estimated using MRAS-Neural Self-Tuning IP obsrever. The simulation results illustrate the good performance and the validity of the proposed observer scheme for practical applications.
PL
W artykule opisano bezczujnikowe sterowanie napędem indukcyjnym bazujące na somostrojacym się oserwatorze wykorzystującym sieć neuronową MRAS. Zazwyczaj przy małych prędkościach wirnika pojawia się błąd pomiaru prędkości. W proponowanej metodzie udaje się ten błąd wyeliminować.
8
EN
In the paper, the concept of universal speed and flux estimator with additional parameters estimators is presented. Proposed solution is based on the Model Reference Adaptive System (MRAS) type flux and speed estimator and can be used in different industrial systems (especially in the automotive applications). Induction Motor (IM) parameters are estimated using the systems based only on simple simulators and adaptive systems (voltage model and current model). Proposed system was tested in the sensorless induction motor drive with the Direct Field Oriented Control (DFOC) algorithm. Simulation and experimental results are presented in the paper.
EN
A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive system (MRAS) scheme is used to estimate the speed and the rotor resistance simultaneously. However, the error between the reference and the adjustable models, which are developed in the stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimates of speed and the rotor resistance from the stator voltage and the machine current measurements. The stator flux components in the stationary reference frame are estimated through a pure integration of the back electro-motive force (EMF) of the machine. When the machine is operated at low speed, the pure integration of the back EMF introduces an error in flux estimation which affects the performance torque and speed control. To overcome this problem, pure integration is replaced with a programmable cascaded low-pass filter (PCLPF). The stability analysis method of the MRAS estimator is verified in order to show the robustness of the rotor resistance variations. Experimental results are presented to prove the effectiveness and validity of the proposed scheme of sensorless ISFOC induction motor drive.
PL
W artykule omówiono możliwość wykrywania uszkodzenia prętów klatki wirnika silnika indukcyjnego z wykorzystaniem metody opartej na identyfikacji parametrów. Technika ta bazuje na założeniu, że wybrane uszkodzenia mogą objawiać się zmianami parametrów silnika, a ich estymacja i obserwowanie tych zmian pozwala na wczesną identyfikację uszkodzenia. Przy czym, w przypadku pęknięcia prętów klatki wirnika, objawem może być wzrost rezystancji schematu zastępczego wirnika. W zaproponowanym podejściu do estymacji rezystancji wirnika wykorzystano układu adaptacyjny z modelem odniesienia (MRAS). Badania silnika indukcyjnego przeprowadzono w bezpośredniej polowo-zorientowanej strukturze sterowania wektorowego. W artykule przedstawiono wyniki badań symulacyjnych, ktore wykonano w środowisku MATLAB/Simulink.
EN
This paper deals with the broken rotor bars detection in squirrel-cage induction motor using parameter identification approach. This technique is based on the assumption, that the chosen failures may result in motor parameters variations. Estimation and observation of parameters changes allows to incipient fault detection. In the case of broken rotor bars, increase of the rotor resistance value may be a good fault symptom. In the proposed system, the rotor resistance estimator is based on the model reference adaptive system (MRAS). The induction motor is operating in the direct field-oriented control structure, under different conditions. Simulation results are performed in MATLAB/Simulink software.
EN
The compensation and detection analysis of rotor faults in a sensorless induction motor drive system with an additional rotor resistance estimator has been conducted and the influence of the rotor faults on the properties of such system has been examined. The rotor flux vector and rotor speed have been reconstructed by the MRASCC estimator. The drive was tested for various conditions. Simulation tests were performed in the direct field oriented control (DFOC) structure realized in the MATLAB/Simulink software.
PL
W artykule opisano możliwości wykorzystania adaptacyjnego regulatora neuronowo rozmytego (ang. Adaptive Neuro Fuzzy Controller - ANFC) w strukturach bezczujnikowego wektorowego sterowania DTC-SVM i DFOC silnika indukcyjnego w charakterze tzw. kompensatora regulatora prędkości kątowej. Przeprowadzono badania eksperymentalne pozwalające na ocenę pracy napędu bezczujnikowego w różnych warunkach pracy. Zwrócono szczególną uwagę na zakres niskich prędkości kątowych, w których napędy tego typu mogą pracować w sposób niestabilny. Do estymacji prędkości i strumienia wirnika/stojana wykorzystano estymator MRASCC. Badania eksperymentalne wykonano przy wykorzystaniu układu szybkiego prototypowania DS1103.
EN
The possibility of application the Adaptive Neuro Fuzzy Controller - ANFC in the structure of sensorless vector controlled induction motor drive (DTC-SVM and DFOC) as a so-called neuro fuzzy speed compensator are presented in the paper. In the paper the experimental results of the vector controlled induction motor drive system under different conditions are presented. Drive operations in the low speed region are presented. To the rotor / stator flux and rotor speed reconstruction the MRASCC estimator is used. DS1103 card is applied in the experimental tests.
EN
The article is a summary of previous work on the possibility of using Petri layers in adaptive neuro-fuzzy controllers. In the first part of the paper the controller and two types of Petri layer have been presented, competitive layer which resets certain signals and transition layer which causes omission of signals. Layer properties were described and comparison has been made. In the second part of the paper, the results of a simulation showing the advantages and disadvantages of proposed solutions have been presented. Both quality of reference signal tracking and energetic cost of control process have been calculated. In the last part, analysis and comments on the results were made. Main conclusions are that transition Petri layer can significantly reduce growth of numerical cost of the algorithm despite the increase of fuzzy rules count. Also both competitive Petri layer and transition Petri layer by changing some inner signals can affect output value of the fuzzy system and thus the control quality indicators change. Most positive solutions have been pointed out
PL
W artykule przedstawiono badania symulacyjne i eksperymentalne pozwalające na ocenę pracy napędu sterowanego metodą DTCSVM przy występowaniu uszkodzeń czujnika prędkości kątowej. Zaproponowano algorytm detekcji uszkodzeń czujnika inkrementalnego i opracowano kompletną strukturę napędu odpornego na uszkodzenia tego elementu. Badania symulacyjne wykonano w środowisku Matlab/Sim Power System a badania eksperymentalne przy wykorzystaniu układu szybkiego prototypowania DS1103. Zaproponowane rozwiązanie może być z powodzeniem wykorzystane w systemach FTC (Fault Tolerant Control).
EN
In the paper the simulation and experimental results of the Direct Torque Control (DTC-SVM) of induction motor drive system under speed sensor faults are presented. Faults detection algorithm is developed. The simulation tests carried out in Matlab/Sim Power System software, DS1103 card is applied in the experimental tests. The proposed solution can be successfully applied in the fault tolerant drive systems.
EN
This article discusses the issue of a single IGBTs open-circuit fault diagnosis problem in voltage source inverters feeding modern electric motor drives. In the first stage of simulation tests the analysis of selected state variable transients relating to the field oriented controlled induction motor drive operation under inverter fault was presented, and then some simulation results of the modeled diagnostic system were introduced.
PL
W artykule omówiono problem diagnostyki uszkodzeń polegających na braku przewodzenia prądu jednego z tranzystorów falownika napięcia we współczesnych napędach elektrycznych. W pierwszej części badań symulacyjnych przeprowadzono analizę wybranych zmiennych stanu w bezczujnikowym napędzie indukcyjnym z bezpośrednim sterowaniem polowo zorientowanym, w którym przekształtnik uległ uszkodzeniu, a następnie przedstawiono wyniki testów zamodelowanego układu diagnostyki awarii.
EN
In the paper the influence of the chosen sensors faults (rotor speed and stator current sensors) to the properties of vector controlled induction motor drive system are tested. Faults detection algorithms based on the simple signals from internal control structure are developed. The simulation tests carried out in Matlab/SimPowerSystem software. The proposed solution can be successfully applied in the fault tolerant drive systems.
EN
In the paper the influence of the chosen sensors faults (rotor speed and stator current sensors) to the properties of induction motor drive system working in the Direct Field Oriented Control structure (DFOC) were tested. Simulations results carried out in Matlab/SimPowerSystem software. Study results contains an analysis of the state variables such as: mechanical and estimated speed, electromagnetic torque, stator's phase currents and rotor flux. Additionally the usage of these signals to develop faults detection algorithms were tested.
EN
In the paper the issues related to the application of adaptive neuro-fuzzy controller for speed controller of an electrical motor are considered. Adaptive control structure with reference model (MRAS) is used. The standard controller is modified by the implementation of competitive Petri layers into its internal structure. The proposed modification improves the properties of the drive compared to the control structure with standard neuro-fuzzy controller. Theoretical considerations are confirmed by simulation studies experimental tests done on the laboratory stand.
EN
This paper presents a novel speed estimator using Reactive Power based Model Reference Neural Learning Adaptive System (RP-MRNLAS) for sensorless indirect vector controlled induction motor drives. The Model Reference Adaptive System (MRAS) based speed estimator using simplified reactive power equations is one of the speed estimation method used for sensor-less indirect vector controlled induction motor drives. The conventional MRAS speed estimator uses PI controller for adaptation mechanism. The nonlinear mapping capability of Neural Network (NN) and the powerful learning algorithms have increased the applications of NN in power electronics and drives. This paper proposes the use of neural learning algorithm for adaptation in a reactive power technique based MRAS for speed estimation. The proposed scheme combines the advantages of simplified reactive power technique and the capability of neural learning algorithm to form a scheme named “Reactive Power based Model Reference Neural Learning Adaptive System” (RP-MRNLAS) for speed estimator in Sensorless Indirect Vector Controlled Induction Motor Drives. The proposed RP-MRNLAS is compared in terms of accuracy, integrator drift problems and stator resistance versions with the commonly used Rotor Flux based MRNLAS (RF-MRNLAS) for the same system and validated through Matlab/Simulink. The superiority of the RP-MRNLAS technique is demonstrated.
EN
Rotational speed difference is an important factor that effects synchronism and stability of vibratory machines. This paper establishes the motor dynamical differential equation based on MRAS (model reference adaptive system). Speed regulator is designed based on PID regulator and adaptive controller. Then using MRAS to control, identify and simulate the speed of two rotors. Simulation results show that adopting MRAS is better than common PID system.
PL
W artykule przedstawiono równania różniczkowe opisujące dynamikę silnika synchronicznego bazujące na MRAS (model reference adaptive system). Następnie opracowano system kontroli szybkości bazujący na sterowniku PID i sterowniku adaptacyjnym.
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