Dynamic Eccentricity Fault Research Articles

Analytical Investigation of Electromagnetic Vibration in Interior Permanent Magnet Synchronous Motors With Dynamic Eccentricity Fault

Analytical Investigation of Electromagnetic Vibration in Interior Permanent Magnet Synchronous Motors With Dynamic Eccentricity Fault

An Expeditious Algorithm for Identification and Classification of Rotor Faults in Salient Pole Synchronous Generators

Providing secure electricity depends on the reliable operation of the synchronous generators in power plants. Inter-turn short circuit (ITSC) and dynamic eccentricity (DE) faults are among the most prevalent fault types in wound field synchronous generators (WFSGs). Among the various signals used to detect faults such as current, voltage, and vibration, the stray magnetic field provides higher sensitivity for early-stage ITSC and DE detection. The introduced detection methods rely on comparison of various signals frequency spectrum's from fault and healthy generators. However, obtaining a frequency spectrum of a healthy synchronous generator that has been operating for decades in a power plant is almost impossible. A unique pattern is introduced using fast Fourier transform that can be implemented on a low-end microcontroller and ideal for IoT solutions. The efficacy of the proposed pattern is examined by finite element modeling and validated on a 100 kVA WFSG setup in the laboratory and field test in a power plant with a power rating of 22 MVA.

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.

Stator current signal crossing for fault diagnosis of self-excited induction generators

This paper presents a novel method for modelling and diagnosis of electrical and mechanical faults in fixed-Speed Self-Excited Induction Generators (SEIGs) operating in autonomous mode in a small-scale wind energy system. The proposed method is validated using the finite element method. After the selection of the magnetising capacitors, the self-excitation process is performed under no-load conditions. Once the stator voltage is established, a symmetrical three-phase load is connected. The fault detection method introduced here is called Stator Current Signal Crossing (SCSC). The SCSC extracts a new signal from the stator currents, that enables the detection of stator inter turn shortcircuits, broken rotor bars, and dynamic eccentricity faults in SEIGs. A spectral analysis of SCSC using the Fast Fourier Transform (FFT) algorithm is used to precisely locate the induced fault components. What sets this fault-tracking method apart from its predecessors is its exceptional ability to detect faults of any magnitude by analysing the modulation of the SCSC signal. These faults are directly identified by the presence of distinct harmonics, each indicative of a specific type of fault. This study also focuses on the SEIG in a wind energy system, whereas previous works have mainly addressed the induction machine in motor mode. In contrast, previous methods involved analysing a single current signal and isolating specific harmonics from a wide frequency range. The effectiveness of the proposed fault detection method and the self-excitation process are illustrated by simulation results and spectral analysis.

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.

Experimental Simulation and Electromechanical Characterization of Dynamic Air Gap Eccentricity Faults inPMSG

This paper presents a designed experimental simulation scheme for dynamic air gap eccentricity (DAGE) faults in permanent magnet synchronous generator (PMSG), along with the testing of their electromechanical characteristics. Unlike previous studies, this paper proposes and applies an experimental device setting scheme that enables accurate and convenient calibration of the DAGE fault degree, offering a novel solution for practical DAGE simulation. The experimental unit measures the electromechanical characteristics of the PMSG before and after the DAGE fault, taking into account the influence of load. The mechanical parameter considered is the stator vibration, while the electrical parameter is the circulating current parallel branches (CCPB) inside the stator winding. The characteristic frequencies of stator vibration and CCPB under the DAGE fault are analyzed based on the experimental results and verified through theoretical calculations and finite element analysis (FEA). The findings demonstrate the effectiveness of the proposed DAGE experimental device. Moreover, DAGE failure increases the strength of stator vibration and introduces new frequency components, namelyfrand 2f ± fr. Under normal operation, the PMSG exhibits no CCPB. However, DAGE faults cause CCPB with frequency components off ± fr. Moreover, the severity of the fault degree positively correlates with larger root‐mean‐square (RMS) values and characteristic frequency amplitudes of stator vibration and CCPB. Furthermore, the amplitude of stator vibration and CCPB decreases with increasing load. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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.

An effective Hilbert-Huang transform-based approach for dynamic eccentricity fault diagnosis in double-rotor double-sided stator structure axial flux permanent magnet generator under various load and speed conditions

Eccentricity fault in double-sided axial flux permanent magnet generator is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic, especially at the initial stages of the fault occurrence. In addition, one of the most important problems in any fault diagnosis approach is the investigation of load and speed variation on the proposed indices. To overcome the aforementioned difficulty and problems, this paper adopts a novelty detection algorithm based on Hilbert-Huang transform (HHT) which is a time-frequency signal analysis approach based on empirical mode decomposition and the Hilbert transform. It is well suited for reliable fault diagnosis since it is unaffected by transient conditions which make the diagnosis process incur into false alarms. The HHT-based methods has been demonstrated in recent years for rotor and bearing faults detection of induction machine and also for stator faults identification in PM synchronous machines with radial flux structure. This study explores the possibility of applying the technique to the detection of dynamic eccentricity faults in double-rotor double-sided stator structure axial flux permanent magnet generator under variable load and speed conditions. This approach relies on two steps: estimating the intrinsic mode functions (IMFs) by the empirical mode decomposition (EMD) and computing the instantaneous amplitude (IA) and instantaneous frequency (IF) of IMFs using the Hilbert transform. The more significant IMFs are determined by means of Hilbert spectrum, which is applied for accurate eccentricity fault diagnosis. The eccentricity severity can be evaluated based on the IMFs energy value. The theoretical basis of the proposed method is presented. The effectiveness of the proposed method is verified by a series of simulation and experimental tests under different conditions. The results show that the presented approach in this paper is robust against load and speed variations.

Fault Mechanism Analysis of Irreversible Demagnetization Due to the Dynamic Eccentricity of IPMSM for EV Traction

The dynamic eccentricity fault (DEF) of the interior permanent magnet synchronous motor (IPMSM) is mainly caused by external mechanical shock. In the case of DEF, an unbalanced magnetic force occurs because the length of the air gap is not constant. Noise and vibration of the motor occur due to unbalanced magnetic force. In addition, since the length of the air gap is not constant, the distribution of magnetic flux density is distorted, and iron loss is increased. As the iron loss increases, the temperature rises, and an irreversible demagnetization fault (IDF) of the permanent magnet occurs due to overheating. Therefore, in this paper, the fault mechanism of IDF due to DEF of IPMSM for electric vehicle (EV) traction is analyzed. Initially, the magnetic flux density and iron loss characteristics according to the healthy condition and DEF condition are analyzed using the finite element method (FEM). Then, the detailed iron loss analysis is performed based on the phase current waveform measured through the load test of the motor. Finally, the fault mechanism of IDF due to DEF was verified through an electric-axle load test on a manufactured motor having eccentricity.

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

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

Diagnostically Oriented Experiments and Modelling of Switched Reluctance Motor Dynamic Eccentricity

The article compares the results of experimental and modelling research of switched reluctance motor at two different operational states: one proper and one with mechanical fault, i.e., with dynamic eccentricity of the rotor. The experiments were carried out on a test bench and then the results were compared with mathematical modelling of quasi-static and dynamic analysis of 2D geometry model. Finally, it was examined how the operation with dynamic eccentricity fault of the motor affected its main physical parameter—the phase current. The analysis was presented in the frequency domain using the Fast Fourier Transform (FFT); however, individual current waveforms in the time domain are also shown for comparison. Applying results of the research could increase reliability of the maintenance of SRM and enhance its application in vehicles for special purposes as well as its military and industrial applications.

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.

Diagnosis and detection of dynamic eccentricity fault for permanent magnet transverse flux generator

The authors analyse no-load and full-load performance of a permanent magnet transverse flux generators (PMTFGs) in fully aligned condition as well as under different types of mechanical faults including static eccentricity (SE), dynamic eccentricity (DE), inclined rotor (IR) and run-out (RO) faults. An analytical model is developed to calculate the air-gap permeance. This permeance is used to estimate the flux density and back-electromotive force in the healthy and faulty machine. Performance of the machine is predicted using the proposed analytical model and verified by comparing it with the results obtained using three-dimensional time stepping finite element method. Finally, the spectra of stator current in the PMTFG under SE, DE, IR and OR faults are determined through which the amplitude of side-band components with a specific frequency pattern is extracted. It can detect the eccentricity fault precisely, recognise its type and determines its severity.

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.

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.

Conditional Monitoring of Switched Reluctance Motor for Static and Dynamic Eccentricity Faults with Fault Isolation

In this paper, the proposed technique interlinking Proteus and Arduino is a novel and cost-effective strategy helps to identify the fault and protect the machine by giving the signal for isolation from supply, it is suitable for all industrial applications. The fault tolerance of the switched reluctance motor is high, but cannot be acclaimed for absolute and should be analyzed under different operating conditions. It is preliminary to examine and diagnose the eccentricity to achieve the smooth running of the motor. The Emulation results for the proposed model successfully exhibited the type of fault, location and also give the details of emergency of repair in a particular section based on the severity of fault in that location. This is a simple and powerful integrated technique feasible to use in all types of laboratory, industrial and research and development applications.

Anti-Interference and Location Performance for Turn-to-Turn Short Circuit Detection in Turbo-Generator Rotor Windings

Online and location detection of rotor winding inter-turn short circuits are an important direction in the field of fault diagnosis in turbo-generators. This area is facing many difficulties and challenges. This study is based on the principles associated with the U-shaped detection coil method. Compared with dynamic eccentricity faults, the characteristics of the variations in the main magnetic field after a turn-to-turn short circuit in rotor windings were analyzed and the unique characteristics were extracted. We propose that the degree of a turn-to-turn short circuit can be judged by the difference in the induction voltage of the double U-shaped detection coils mounted on the stator core. Here, the faulty slot position was determined by the local convex point formed by the difference in the induced voltage. Numerical simulation was used here to determine the induced voltage characteristics in the double U-shaped coils caused by the turn-to-turn short circuit fault. We analyzed the dynamic eccentricity fault as well as combined the fault of a turn-to-turn short circuit and dynamic eccentricity. Finally, we demonstrate the positive anti-interference performance associated with this fault detection method. This new online detection method is satisfactory in terms of sensitivity, speed, and positioning, and overall performance is superior to the traditional online detection methods.

Induction Motors Dynamic Eccentricity Fault Diagnosis Based on the Combined Use of WPD and EMD-Simulation Study

The frequency-domain analysis using the fast Fourier transform (FFT) for diagnosis of eccentricity fault has been widely used in squirrel-cage induction motor (IM). However, with the restriction of sampling frequency and time acquisition, FFT analysis could not provide ideal results under low levels of dynamic eccentricity (DE). In this paper, a combined use of the wavelet packet decomposition (WPD) and empirical mode decomposition (EMD) method is presented to diagnose the IM fault under low degrees of purely DE. The proposed method is based on the decomposition of apparent power signal and extracts the characteristic component. The fault severity factor (FSF) has been defined to evaluate the eccentricity severity. Simulation results using the finite element method (FEM) are tested to verify the effectiveness of the presented method under different load conditions.

Analytical Technique for Analysis and Detection of Eccentricity Fault in Surface-Mounted Permanent Magnet Generators Using No-Load Voltage Signature

This paper presents a method for modeling the effects of static eccentricity, dynamic eccentricity, and mixed eccentricity faults on the electromotive force (emf) of the surface-mounted permanent magnet generators (SMPMGs). The model is based on the combination of conformal mapping method (complex relative permeance) and eccentricity relative air gap permeance and it presents explicit formulas for no-load magnetic field distribution, magnetic flux, and emf in SMPMGs under different eccentricity fault types, some have not been so far considered elsewhere. The analytical and also numerical results show that there are some side-band components in the emf signature which can be used as eccentricity fault index. Analytical results validate by time-stepping finite element method (TSFEM) results.

Dynamic Eccentricity Fault Diagnosis in Induction Motors Using Finite Element Method and Experimental Tests

This paper presents the dynamic eccentricity (DE) in the squirrel cage induction machine obtained by the simulation using finite element method (FEM) and the experimental tests. Motor current signature analysis (MCSA) through the power spectral density (PSD) is used to monitor the low frequency components related to the rotor faults. In order to generalise the study, a comparison was performed between faulty machines and healthy, under different load conditions. The experimental tests show the encountered difficulties in the detection of the dynamic eccentricity under various load conditions because the spectral representation shows the existence of low frequency components for the healthy case, which are superimposed with the indicator components. These low frequency components offer an alternative way to the monitoring of eccentricity air-gap when the load is balanced.