Rotor Inter-turn Short Circuit Fault Research Articles

Analysis on Rotor Vibration Characteristics under Dynamic Rotor Interturn Short Circuit Fault in Synchronous Generators

A dynamic rotor interturn short circuit fault may occur during synchronous generator operation. However, there is no method to analyze the generator’s characteristics under the dynamic rotor interturn short circuit fault and identify the fault. In order to solve this problem, a new dynamic rotor interturn short circuit fault analysis model is creatively proposed through mathematical derivation. Firstly, the rotor vibration characteristics and the mechanical response under magnetic pull excitation are theoretically analyzed. In addition, a finite element modeling method for the dynamic rotor interturn short circuit fault is proposed, and an experimental device is designed. The model of a synchronous generator under the dynamic rotor interturn short circuit fault is established to obtain the rotor’s unbalanced magnetic pulls and mechanical responses by finite element calculation. Finally, the rotor vibrations are tested on a CS-5 prototype generator. The validity of the model is verified by finite element calculation and an experiment. This paper provides theoretical support for the diagnosis of a synchronous generator’s dynamic rotor interturn short circuit fault.

Stator current identification in generator among single and composite faults composed by static air‐gap eccentricity and rotor inter‐turn short circuit

In this study, a fault diagnosis model based on magnetic density is proposed to analyse the current characteristics of synchronous generator rotor inter-turn short circuit and air gap eccentric single fault and composite fault. The model considers the influence of rotor inter-turn short circuit and air gap eccentricity on air gap magnetic density. According to two main factors, the short circuit turns and eccentric distance, are used to reflect the short circuit and eccentricity of the generator. The detailed parameter input model of the generator can easily and quickly predict the development trend of these current parameters based on the air gap magnetic density. And the phase current is selected as the current parameter. The validity of the proposed model is verified by two-dimensional finite element analysis and experimental research.

A Novel Universal Model Considering SAGE for MFD-Based Faulty Property Analysis Under RISC in Synchronous Generators

This article proposes a new rotor interturn short circuit (RISC) fault analysis model for the electromechanical property study in synchronous generators. The specific novelty of this model lies in two aspects: First, It considers that most generators exist static air-gap eccentricity (SAGE), so it analyzes the RISC fault under normal and SAGE, making the model more versatile, and second, it takes into account not only the short circuit degree, but also the short circuit position, consequently it is more universal. By feeding the number of short circuit turns (denotes the short circuit degree), the angle between the two slots, where the short circuit takes place (denotes the short circuit position) and the detailed parameters of the generator into the model, the developing tendency of the key magnetic flux density (MFD)-based parameters can be conveniently predicted. The advantages of the proposed model primarily lie in the universality and the calculation speed. It can quickly evaluate the generator operating conditions. The phase current and the electromagnetic torque are selected in this article as the representatives of the electrical parameter and the mechanical parameter, respectively. Two-dimensional finite element analysis and experimental studies validate the proposed model.

Electromagnetic Torque Fluctuating Properties under Dynamic RISC Fault in Turbogenerators

This paper analyzes the electromagnetic torque (EMT) fluctuation characteristics in synchronous generators under rotor interturn short-circuit (DRISC) fault. The novelty of this paper is that the DRISC fault is proposed based on the intermittent interturn short circuit existing in the actual operation and compared with the static rotor interturn short-circuit (SRISC) fault. In the work, by studying the influence of DRISC with different positions and different short-circuit degrees, the fluctuation characteristic of the EMT is analyzed and verified. The results show that when the DRISC5% fails, the location is in slot 3, the amplitude of first harmonic decreases by 7.2%, second harmonic amplitude increases by 33.4%, third harmonic decreases by 4.3%, and fourth harmonic increases by 26.8%. As the degree increased and positioned away from the large tooth of the DRISC, the overall EMT amplitude and reverse pulse increased, first and third harmonics decreased, and second and fourth harmonics increased.

Detection of Interturn Short-Circuit Faults in DFIGs Based on External Leakage Flux Sensing and the VMD-RCMDE Analytical Method

Fault detection based on external leakage flux can address various faults, such as short circuit faults in stators and rotors. External leakage flux sensing technology, as a noninvasive method, has been attracting increasing attention and research. However, for a high-power doubly fed induction generator (DFIG), the external leakage flux signals of the generator are easily overwhelmed by a strong noise background, and the fault diagnosis and recognition of stator and rotor interturn short circuits is complicated, which limits the practical engineering application of leakage flux sensing technology. Aiming at addressing interturn short circuit faults in DFIGs, this paper proposes a method for fault feature extraction and recognition of stator and rotor short circuits based on variational mode decomposition (VMD) and the refined composite multiscale dispersion entropy (RCMDE) analytical method for the external flux leakage of the generator. The optimized parameters of VMD are selected automatically by the genetic algorithm (GA), and VMD is adopted to adaptively decompose the external leakage flux signals into a series of intrinsic mode function (IMF) components. The evaluation criterion based on the correlation number in the frequency domain combined with the autocorrelation function is used to select the best IMF components with clear features. Two different components are chosen to reconstruct the flux leakage signal. The characteristic frequency of the reconstructed signal is analyzed by the Hilbert-Huang transform (HHT) and the total harmonic effective value of the characteristic component. To effectively identify and diagnose the generator stator and rotor interturn short circuit fault, RCMDE is used for the flux leakage reconstructed signal. The experimental results under different stator and rotor short-circuit levels show that this diagnosis method can effectively extract the weak feature information from the external flux leakage signals and perform fault feature extraction and recognition for stator and rotor short circuits.

Enhanced Characteristic Vibration Signal Detection of Generator Based on Time-Wavelet Energy Spectrum and Multipoint Optimal Minimum Entropy Deconvolution Adjusted Method

To overcome the shortage of low SNR (signal to noise ratio) of the multipole generator vibration signal which brings rigid difficulty to the fault diagnosis, a new method which combines the Time-Wavelet Energy Spectrum (TWES) with the Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) algorithm is proposed. This method uses TWES to extract and enhance the characteristic signal, while employing MOMEDA to optimize the spectrum structure and filter the noise. The application of this method to the simulating signal as well as the test stator vibration signal in a 6-pole generator before and after rotor interturn short circuit fault validates the effectiveness of the method. Moreover, the comparison among the proposed method and some other general methods such as the Empirical Mode Decomposition (EMD) and the maximum correlative kurtosis deconvolution (MCKD) suggests that the proposed method is superior to these methods.

Impacts of rotor inter-turn short circuit fault upon performance of wound rotor induction machines

This paper investigates the performance of a wound rotor induction motor (WRIM) under rotor inter-turn short circuit (SC) fault. Magnetic equivalent circuit (MEC) and finite elements method (FEM) are used to model the machine. Impacts of the fault on the signals of the machine including rotor current, stator current, and developed torque of the motor are addressed. Current of SC turns is also the signal that is considered here. A method based on the MEC is used to estimate different inductances of WRIM in which the impact of yokes, stator and rotor tooth, windings distribution and also core saturation are included. The obtained inductances are compared with that of the FEM and effect of the SC turns on the inductances are investigated. Finally, the fault is diagnosed using Fourier transform of the stator current and verified by experimental results.

Stator Vibration Characteristic Identification of Turbogenerator among Single and Composite Faults Composed of Static Air-Gap Eccentricity and Rotor Interturn Short Circuit

This paper investigates the radial stator vibration characteristics of turbogenerator under the static air-gap eccentricity (SAGE) fault, the rotor interturn short circuit (RISC) fault, and the composite faults (CFs) composed of SAGE and RISC, respectively. Firstly, the impact of the faulty types on the magnetic flux density (MFD) is analyzed, based on which the detailed expressions of the magnetic pull per unit area (MPPUA) on the stator under different performing conditions are deduced. Then, numerical FEM simulations based on Ansoft and an experimental study are carried out, taking the SDF-9 type fault simulating generator as the study object. It is shown that SAGE will increase the stator vibration at 2f(fis the electrical frequency) which already exists even in normal condition, while RISC and CF will bring in stator vibrations atf, 2f, 3f, and 4fat the same time. The vibration amplitudes under CF are larger than those under RISC. As SAGE increases, the vibration amplitudes of each harmonic component under CF will all be increased, while the development of RISC will decrease the 2nd harmonic vibration but meanwhile increase the 4th harmonic vibration. The achievements of this paper are beneficial for fault identification and condition monitoring of the turbogenerator.

Magnetic Field Finite Element Analysis of Generator with Rotor Inter-Turn Short-Circuit Fault

Rotor inter-turn short-circuit is a common fault in generator and it is a research hotspot to identify the fault at its early stage. Considering the disadvantage of circuit analytical method, this paper establishes a 2D transient finite element electromagnetic-circuit coupling model, and calculates the magnetic field at normal and fault situations through the powerful post-processing function of ANSOFT, then magnetic flux density cloud pictures and air-gap magnetic flux density curves of different operating conditions are got. Using MATLAB to analyze and deal with the air-gap flux density cures, we can get the differences of faults in different levels and different positions, which provide a basis for further study of rotor inter-turn short-circuit fault.