Токовая диагностика эксцентриситета ротора асинхронных двигателей

В статье рассматриваются вопросы мониторинга и диагностики асинхронных двигателей с короткозамкнутым ротором. Показано, что наличие эксцентриситета ротора отрицательно влияет на энергетические характеристики асинхронных двигателей. Обосновано целесообразность упреждающей диагностики, что позволяет заблаговременно выявить дефекты на ранней стадии их развития

Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

Nowadays, industrial plants are calling for high-performance fault diagnosis techniques to meet stringent requirements on system availability and safety in the event of component failures. This paper deals with robust fault estimation problems for stochastic nonlinear systems subject to faults and unknown inputs relying on Takagi-Sugeno fuzzy models. Augmented approach jointly with unknown input observers for stochastic Takagi-Sugeno models is exploited here, which allows one to estimate both considered faults and full system states robustly. The considered unknown inputs can be either completely decoupled or partially decoupled by observers. For the un-decoupled part of unknown inputs, which still influence error dynamics, stochastic input-to-state stability properties are applied to take nonzero inputs into account and sufficient conditions are achieved to guarantee bounded estimation errors under bounded unknown inputs. Linear matrix inequalities are employed to compute gain matrices of the observer, leading to stochastic input-to-state-stable error dynamics and optimization of the estimation performances against un-decoupled unknown inputs. Finally, simulation on wind turbine benchmark model is applied to validate the performances of the suggested fault reconstruction methodologies

Non-invasive load monitoring of induction motor drives using magnetic flux sensors

Existing load monitoring methods for induction machines are generally effective, but suffer from sensitivity problems at low speeds and non-linearity problems at high supply frequencies. This study proposes a new noninvasive load monitoring method based on giant magnetoresistance flux sensors to trace stray flux leaking from induction motors. Finite element analysis is applied to analyse stray flux features of test machines. Contrary to the conventional methods of measuring stator and/or rotator rotor voltage and current, the proposed method measures the dynamic magnetic field at specific locations and provides time-spectrum features (e.g. spectrograms), response time load and stator/rotor characteristics. Three induction motors with different starting loading profiles are tested at two separate test benches and their results are analysed in the time-frequency domain. Their steady features and dynamic load response time through spectrograms under variable loads are extracted to correlate with load variations based on spectrogram information. In addition, the transient stray flux spectrogram and time information are more effective for load monitoring than steady state information from numerical and experimental studies. The proposed method is proven to be a low-cost and non-invasive method for induction machine load monitoring

Influence of manufacturing tolerances and eccentricities on the unbalanced magnetic pull in permanent magnet synchronous motors

Eccentricity is an inevitable fault in electric motors and hence its diagnosis is an important topic. Thus, the influence of static and dynamic eccentricities on the harmonics of the frequency spectra of the unbalanced magnetic pull is analyzed.In this study, dimensional tolerances of the rotor and the stator are also considered. All parts have dimensional tolerances in their designs and their real magnitudes vary to some extent from the theoretical values after the manufacturing process. Thanks to the finite element simulations, verified with experimental results, it is observed that the deviations originated by the manufacturing tolerances produce changes in the amplitudes of some harmonics and also additional and characteristic harmonics in the frequency spectra of the unbalanced magnetic pull. These are not negligible and must be taken into account when robust eccentricity detection procedures are defined. Otherwise, harmonics originated by tolerances and by eccentricities can be misidentified

Current-Based Detection of Mechanical Unbalance in an Induction Machine Using Spectral Kurtosis with Reference

This article explores the design, on-line, of an electrical machine’s healthy reference by means of statistical tools. The definition of a healthy reference enables the computation of normalized fault indicators whose value is independent of the system’s characteristics. This is a great advantage when diagnosing a broad range of systems with different power, coupling, inertia, load, etc. In this paper, an original method called spectral kurtosis with reference is presented in order to designa system’s healthy reference. Its principle is first explained on asynthetic signal. This approach is then evaluated for mechanicalunbalance detection in an induction machine using the stator currents instantaneous frequency. The normalized behaviour ofthe proposed indicator is then confirmed for different operatingconditions and its robustness with respect to load variationsis demonstrated. Finally, the advantages of using a statisticalindicator based on a healthy reference compared to a raw faultsignature are discussed

Detection of eccentricity faults in five-phase ferrite-PM assisted synchronous reluctance machines

Air gap eccentricity faults in five-phase ferrite-assisted synchronous reluctance motors (fPMa-SynRMs) tend to distort the magnetic flux in the air gap, which in turn affects the spectral content of both the stator currents and the ZSVC (zero-sequence voltage component). However, there is a lack of research works dealing with the topic of fault diagnosis in multi-phase PMa-SynRMs, and in particular, focused to detect eccentricity faults. The analysis of the spectral components of the line currents and the ZSVC, allows developing fault diagnosis algorithms to detect eccentricity faults. The effect of the operating conditions is also analyzed, since this paper shows that it has a non-negligible impact on the effectivity and sensitivity of the diagnosis based on the analysis of the stator currents and the ZSVC. To this end, different operating conditions are analyzed. The paper also evaluates the influence of the operating conditions on the harmonic content of the line currents and the ZSVC, and determines the most suitable operating conditions to enhance the sensitivity of the analyzed methods. Finally, fault indicators to detect eccentricity faults, which are based on the spectral content of the stator currents and the ZSVC are derived, and their performance is assessed. The approach presented in this work may be useful to develop fault diagnosis strategies based on the acquisition and subsequent analysis and interpretation of the spectral content of the line currents and the ZSVC.Peer ReviewedPostprint (published version