Static Eccentricity Fault Research Articles

State-space model for induction motors with static eccentricity faults

State-space model for induction motors with static eccentricity faults

Impact of 3D air gap eccentricity on winding insulation temperature characteristic in PMSG

The static air gap eccentricity is one of the prevalent faults in permanent magnet synchronous generators. In previous studies, the variation of magnetic flux density, stator current and vibration have been studied mostly. However, the temperature characteristic of winding insulation under 3D static air gap eccentricity fault is rarely investigated. As a supplement, this paper comprehensively analyzes the influence of radial static air gap eccentricity, axial static air gap eccentricity and the combined static air gap eccentricity (radial static air gap eccentricity and axial static air gap eccentricity) fault on the winding insulation thermal response. The whole work is based on not only the loss of core and windings but also the temperature rise of the winding insulation, which is carried out through theoretical analysis, finite element calculation, and experiment verification. It is shown that radial static air gap eccentricity will increase the winding insulation temperature whatever in singe radial static air gap eccentricity or combined static air gap eccentricity, while axial static air gap eccentricity has the opposite effect. Specifically, the winding insulation temperature in radial static air gap eccentricity 0.1 mm, 0.2 mm and 0.3 mm cases are 57.18℃, 59.10℃ and 61.04℃, respectively, which is 3.29℃, 5.21℃ and 7.15℃ higher than that under normal condition. However, under axial static air gap eccentricity, winding insulation temperature will decrease by 1.84℃, 4.11℃ and 5.9℃, respectively. When axial static air gap eccentricity is unchanged and radial static air gap eccentricity is increased, the winding insulation temperature will increase by 1.5℃ and 3.23℃, respectively. On the contrary, when radial static air gap eccentricity is unchanged and axial static air gap eccentricity increases, the winding insulation temperature decreases by 2.54℃ and 5.66℃, respectively. The end part and the join between the end and line parts of the winding insulation are the most dangerous positions to suffer from static thermal wear.

Analysis and effect of static eccentricity fault on performance indicators of a synchronous reluctance motor

Analysis and effect of static eccentricity fault on performance indicators of a synchronous reluctance motor

Robust Design Optimization Considering Static Eccentricity Fault of Six-Phase IPMSM

Robust Design Optimization Considering Static Eccentricity Fault of Six-Phase IPMSM

Empirical mode decomposition and Hilbert–Huang transform-based eccentricity fault detection and classification with demagnetization in 120 kW interior permanent magnet synchronous motors

Permanent magnet synchronous motors (PMSMs) are extensively used in electric vehicles (EVs) owing to their high power density and efficiency. However, their safety and reliability have not been verified sufficiently. Failure of PMSMs in EVs can cause performance degradation, increased maintenance costs, and catastrophic accidents. Therefore, early detection of faults in PMSMs is necessary for an efficient and safe operation. In this study, static, dynamic, and mixed eccentricity faults in 120 kW interior permanent magnet synchronous motors (IPMSMs) were diagnosed and distinguished from uniform demagnetization fault by monitoring the Hilbert spectrum of the stator current. Experiments were carried out for different speeds, loads, and fault severities to analyze the effect of operating conditions on the proposed fault detection method. The phase current data were decomposed into set of intrinsic mode functions (IMFs) with empirical mode decomposition (EMD) method and Hilbert transform was applied for each IMFs to calculate the instantaneous frequency and energy. The resultant Hilbert spectrum exhibited instantaneous frequency distortions with an instantaneous energy surge under an eccentricity fault. The effect of thresholding in EMD was analyzed to improve the accuracy of the proposed method under high-load and high-speed conditions. Also, the experimental results showed that eccentricity and uniform demagnetization faults can be classified by monitoring the overall instantaneous energy.

A mathematical analytical modeling method for rotor eccentricity fault of large VSPSU

Aiming at the rotor eccentric fault modeling problem of large VSPSU (VSPSU), a mathematical analytical modeling method based on air gap magnetic field analysis is proposed. This method uses Fourier series decomposition to represent the air gap permeability of static and dynamic eccentricity faults. Then, taking a single coil as a unit, the eccentric self-inductance coefficients between each branch of the windings are derived. Furthermore, the mathematical analytical modeling of the eccentric fault is completed by combining the voltage and flux formulas of each winding branch. The model can reliably reflect the typical fault characteristics of large VSPSUs with eccentric faults, which can provide an analysis basis for subsequent relay protection research.

Static and Dynamic Eccentricity Faults Diagnosis in PM Synchronous Motor Using Planar Search Coil

Eccentricity fault in electrical motor causes increased noise and vibration, and degradation of motor characteristics. Thus, early detection of the eccentricity fault is required. Motor current signal analysis, a common fault detection method, may fail to detect eccentricity faults, depending on the type of eccentricity. This paper proposes an eccentricity fault detection method using a new planar search coil (PSC). The model of PSC and the contribution of eccentricity to PSC are presented. PSC is a new type of search coil that generates a voltage signal from magnetic flux. The output signal of PSC is changed by the inductance deviation, a result of the rotor eccentricity. Finally, the experimental verification of fault detection using PSC is shown. The eccentricity fault detection method using PSC is proven to diagnose both dynamic eccentricity and static eccentricity faults.

The Neutral Voltage Difference Signal as a Means of Investigating Eccentricity and Demagnetization Faults in an AFPM Synchronous Generator

This article investigates the neutral voltage difference signal, VNO signal, for fault diagnosis. The aforementioned signal is the signal of the voltage between the common star point of the stator and the common star point of the load. The under-study faults are demagnetization and static eccentricity faults, while the machine in which the faults are investigated is an axial flux permanent magnet (AFPM) synchronous generator, suitable for wind power applications. This study was conducted using a 3D finite element method (3D-FEM), and the machine’s FEM model was validated through experiments. This method is one of the most accurate methods for electrical machine computation, allowing for a detailed study of electromagnetic behavior. The components that constitute the VNO signal were determined using a 3D-FEM software program (Opera 18R2). Subsequently, further analysis was performed using MATLAB R2022b software, and a fast Fourier transform (FFT) was applied to this signal. In all the investigated faulty cases, new harmonics appeared, and the healthy amplitudes of most of the already existing harmonics increased. These findings can be used for fault identification. The analysis revealed that the harmonic frequency of 1.5fs was the most dominant in the case of demagnetization, while in the case of static eccentricity, the most dominant harmonic was a frequency equal to the machine’s operating frequency, fs. The novelty of this study is that this signal has not previously been used for fault identification, especially in AFPM synchronous machines. This signal depends on EMF voltage and stator phase currents but is less sinusoidal. Consequently, it can detect faults in cases where the aforementioned signals cannot be used for detection.

Static Eccentricity Fault of Elastic Ring Squeeze Film Damper for Aeroengine

The complete reduced-order model of an aeroengine and diagnosis recognition of the static eccentricity fault of the elastic ring squeeze film damper (ERSFD) is the research topic in this study. The finite element method was to set up the complete dynamic model of the “ERSFD–rolling bearing–double rotor–casing” by considering nonlinear bearing and oil film forces. Based on the Karhunen–Loève orthogonal decomposition reduced theories, the reduced-order model of the complete double-rotor systems is obtained. The improved short-time Fourier transform (STFT) + pseudocolor technology and lightweight network mode EfficientNetV2 realize the static eccentricity fault diagnosis and automatic recognition of the ERSFD. The general expression of oil film force and effective reduced-order model are given. The numerical comparison shows that the degree of freedom was reduced to , and the computational running time was shortened to of the full-order model by analyzing the amplitudes and bifurcations at the front and back supports of the casing. It has the highest recognition accuracy and the shorter automatic recognition time of EfficientNetV2 than other network models. The theories and methods used are of guiding significance for effective vibration modeling and order reduction solution of the complete aeroengine system, as well as dynamic simulation and fault mechanism research.

Impact of Static Air-Gap Eccentricity Fault on Synchronous Generator Efficiency

This paper presents a precise analysis of the efficiency characteristic of the synchronous generator under both normal and SAGE conditions. In this work, various losses of the synchronous generator are computed by the qualitative theoretical model and the finite element analysis in detail. Further, the generator efficiency model is proposed according to the relationship between the output power and the loss. The presented model is verified in a 5-kW non-salient synchronous generator. The result demonstrates that the loss increases and the efficiency reduce as the SAGE intensifies.

Static Eccentricity Fault Location Diagnosis in Resolvers Using Siamese-Based Few-Shot Learning

Static Eccentricity Fault Location Diagnosis in Resolvers Using Siamese-Based Few-Shot Learning

Closed-Loop Drive Detection and Diagnosis of Multiple Combined Faults in Induction Motor Through Model-Based and Neuro-Fuzzy Network Techniques

In this paper, a fault detection and diagnosis approach adopted for an input-output feedback linearization (IOFL) control of induction motor (IM) drive is proposed. This approach has been employed to detect and identify the simple and mixed broken rotor bars and static air-gap eccentricity faults right from the start its operation by utilizing advanced techniques. Therefore, two techniques are applied: the model-based strategy, which is an online method used to generate residual stator current signal in order to indicate the presence of possible failures by means of the sliding mode observer (SMO) in the closed-loop drive. However, this strategy is not able to recognise the fault types and it can be affected by the other disturbances. Therefore, the offline method using the multi-adaptive neuro-fuzzy inference system (MANAFIS) technique is proposed to identify the faults and distinguish them. However, the MANAFIS required a relevant database to achieve satisfactory results. Hence, the stator current analysis based on the HFFT combination of the Hilbert transform (HT) and Fast Fourier transform (FFT) is applied to extract the amplitude of harmonics due to defects occur and used them as an input data set for the MANFIS under different loads and fault severities. The simulation results show the efficiency of the proposed techniques and its ability to detect and diagnose any minor faults in a closed-loop drive of IM.

Static Eccentricity Fault Analysis of Surface-Mounted Permanent Magnet Electromotor with Skewed Slots Based on 2D FEA

It is of significance to analyze the performance of eccentric electromotor for the research on the electric vehicle wheel drive system’s operational reliabilities. We developed a fast equivalent algorithm in which the two-dimensional finite element calculation results are translated into three-dimensional calculation results. An electromotor with skewed slot was decomposed into straight-slot electromotor units that were series-wound. A prototype electromotor driven by square wave current under healthy and eccentric conditions was calculated, and the computation accuracy of the equivalent algorithm was analyzed. The air-gap magnetic field and induced electromotive force were calculated and contrasted. The study results indicate that the magnetic field distribution and the induced electromotive forces of winding elements with different axis positions were affected transparently by grievous eccentricity, yet the induced electromotive force of one phase winding and average value of torque remained virtually invariable. The reference to reliability analysis of electric vehicle wheel drive system is provided.

Advances in Fault Diagnostics and Post‐Fault Operation of Electrical Drives

Advances in Fault Diagnostics and Post‐Fault Operation of Electrical Drives

A Hybrid Method to Diagnose 3D Rotor Eccentricity Faults in Synchronous Generators Based on ALIF_PE and KFCM

This paper proposed a new hybrid diagnosis method for the generator’s 3D static eccentricity faults which include the axial eccentricity, the radial eccentricity, and the mixed eccentricity composed of the former two. Firstly, adaptive local iterative filtering (ALIF) method was used to decompose the vibration signals of the generator under eccentricity faults. Then, in order to figure out the intrinsic mode function (IMF) components with the upmost feature information, the correlation coefficient was calculated. Finally, the components’ permutation entropy (PE) is extracted to construct the eigenvector matrix which can be used to input the kernel fuzzy C-means (KFCM) algorithm to obtain the result of clustering. The result indicates that the classification coefficient based on ALIF and KFCM behaves closer to 1, while the average fuzzy entropy (FE) is closer to 0, showing that this method is able to detect different eccentricity faults more accurately.

Static and dynamic eccentricity fault diagnosis of large salient pole synchronous generators by means of external magnetic field

Although synchronous generators are robust and long-lasting equipment of power plants, consistent electricity production depends on their health conditions. Static and dynamic eccentricity faults are among the prevalent faults that may have a costly effect. Although several methods have been proposed in the literature to detect static and dynamic eccentricity faults in salient pole synchronous generators (SPSGs), they are non-sensitive to a low degree of failure and require a predefined threshold to recognise the fault occurrence that may vary based on machine configuration. This article presents a detailed magnetic analysis of the SPSGs with static and dynamic eccentricity faults by focusing on the external magnetic field. The external magnetic field was measured using two search coils installed on the backside of the stator yoke. Also, advanced signal processing tools based on wavelet entropy were used to analyse the induced electromotive force (emf) in search coils to extract the fault index. The proposed index required no threshold to recognise the starting point of fault occurrence and was sensitive to a low degree of fault. It was also non-sensitive to load variation and noise that may induce a false alarm.

Various parameters influence on field distribution in eccentric disc-type permanent magnet machine based on analytical method

ABSTRACT Eccentricity fault is a common fault in axial flux permanent magnet (PM) machines that can be destructive. The finite element method (FEM) has been already used for modelling eccentricity fault in disc type PM machine. Applying three-dimensional (3D) FEM to this motor is essential. However, 3D-FEM is a very time-consuming technique. Therefore, it is more appropriate to use an analytical technique to investigate the impact of different parameters upon the motor’s performance. The existing analytical methods usually represent a qualitative overview of the faulted machine. In this paper, a precise and quick analytic method is introduced, reflecting the impact of various important parameters, including rotor angle and fault position on the motor’s performance. This method enables the calculation of the induced voltage in a search coil. Comparing the results obtained from the proposed method and FEM, in both the no-load and full-load conditions, confirms the method’s accuracy. Finally, the impact of the search coil’s various parameters on dynamic and static eccentricity faults is examined. In addition, choosing the proper search coil pitch for eccentricity faults detection is discussed.

Analysis of rotor asymmetry fault in three-phase line start permanent magnet synchronous motor

This article proposed a detection scheme for three-phase Line start permanent magnet synchronous motor (LSPMSM) under different levels of static eccentricity fault. Finite element method is used to simulate the healthy and faulty LSPMSM with different percentages of static eccentricity. An accurate laboratory test experiment is performed to evaluate the proposed index. Effects of loading condition on LSPMSM are also investigated. The fault related signatures in the stator current are identified and an effective index for LSPMSM is proposed. The simulation and experimental results indicate that the low frequency components are an effective index for detection of the static eccentricity in LSPMSM.

Study of a Combined Demagnetization and Eccentricity Fault in an AFPM Synchronous Generator

This article investigates the combined partial demagnetization and static eccentricity fault in an Axial Flux Permanent Magnet (AFPM) Synchronous Generator. The machine is simulated using 3D FEM, while the EMF spectrum is analyzed in order to export the fault related harmonics using the FFT analysis. Firstly, the partial demagnetization fault, without the coexistence of eccentricity, and both the static angular and axis eccentricity faults, without the coexistence of partial demagnetization, are studied. In the case of eccentricity fault, the phase EMF sum spectrum has also been used as a diagnostic mean, because, when only eccentricity fault exists in the generator (either angular or axis) new harmonics do not appear in the EMF spectrum. Secondly the combination of partial demagnetization fault with static axis and static angular eccentricity is investigated and different comparisons are made when the demagnetization and the eccentricity level changes. The investigation revealed that the combination of eccentricity and demagnetization creates new harmonics in the EMF spectrum. The novelty of the article is that these combined faults are studied for the first time in the international literature, and the phase EMF sum spectrum has not been previously used for eccentricity diagnosis in this machine type.

Permanent magnet vernier generator under dynamic eccentricity fault: diagnosis and detection

Permanent magnet vernier generators (PMVGs) are suitable for meeting power concussion requirements of traffic enforcement cameras and traffic-driven applications. In this study, the performance of PMVGs at no-load and full-load are analysed in healthy machines and machines under different types of mechanical faults including static eccentricity, dynamic eccentricity, inclined rotor, and run-out faults. Furthermore, an analytical model is developed to estimate the air-gap permeance and the induced voltages in the healthy generator and generator under the above-mentioned mechanical faults. Then, the performance of the generator is predicted using a two-dimensional and three-dimensional time stepping finite-element method. Finally, from the stator current spectrum of the PMVG under dynamic eccentricity fault, the amplitude of the side-band components with a specific frequency pattern is extracted and compared with experimental results.