Eccentricity Fault Detection Research Articles

Eccentricity fault diagnosis indices for permanent magnet machines: state‐of‐the‐art

Eccentricity fault with 10% severity is probably the only existing fault in a brand new healthy electrical machine that is acceptable as a manufacturing tolerance. This fault can be developed due to a continuous pull between stator and rotor, even in a de-energized machine. So, it must be diagnosed,and its severity monitored. The authors introduced and criticized various indices for eccentricity fault diagnosis. Advantages, drawbacks, and ambiguous points of each index and potential ground for improvement of these techniques are addressed. Moreover, different eccentric PM machine modelling techniques are reviewed and environmental factors affecting the eccentricity fault detection process are discussed. This survey covers all direct current and alternating current PM machines. It provides information about the researches performed since 1986 and it is helpful to newcomers to this field, artisans, and protection system designers. Considering the given information, the readers achieve enough understanding of the weaknesses and strong points of each eccentricity fault diagnosis index. Then, these indices are evaluated through assigning weight coefficients under various scenarios. Interested individuals can modify these weight coefficients based on the specifics of the application and decide which index is the most appropriate.

A new analytical technique for analysis and detection of air-gap eccentricity fault in surface-mounted permanent-magnet machines

A new analytical technique for analysis and detection of air-gap eccentricity fault in surface-mounted permanent-magnet machines

Design of a Combined Screening and Damping Layer for a 10-MW-Class Wind Turbine HTS Synchronous Generator

This paper is focused on the design of a single protection layer to cover both the screening and damping characteristics of a large-scale high-temperature superconducting (HTS) wind turbine synchronous generator under sudden short-circuit conditions. Due to small synchronous reactance of HTS generators, short-circuit condition causes substantial fault current in the stator windings, which produces high unbalance variable magnetic field as well as substantial mechanical fluctuations issues. The former one can lead to unstable condition for HTS field windings, due to induced ac loss and field overcurrent, and the latter one can produce large fluctuations on the generator rotational speed and rotor torque angle. The proposed protection layer is designed in a way that not only screening capability is provided for the HTS windings by preventing unbalance magnetic field penetration, but desirable damping ratio is also achieved so that the fluctuations are suppressed in a proper transient time. A 10-MW-class HTS synchronous generator is modeled and simulated using finite element method under different short-circuit conditions. The temperature variation study and field overcurrent analysis are provided to show the compatibility of the proposed model. In addition, magnetic force distribution and static eccentricity fault detection analyses are provided, which guarantee the proper dynamic performance of the studied generator using the proposed protection layer. Simulation results confirm that with the proposed protection layer, both the screening and damping characteristics of the 10-MW-class HTS generator are obtained and proper transient dynamic responses are deduced for wind power applications.

RETRACTED: Detection of eccentricity fault based on vibration in the PMSM

Abstract This paper presents how to diagnose faults in static and dynamic eccentricity of a rotor by observing the vibration of permanent magnet synchronous motor. The radial electromagnetic force density of the permanent magnet synchronous motor is represented as the square of the air-gap flux density based on the Maxwell stress tensor, which is applied to the stator to cause the vibration. The distribution of air-gap flux density changes with the static and dynamic eccentricity so the changes of vibration order and frequency of radial electromagnetic force density will be considered with formulas. In result, the static eccentricity changes the vibration order while the dynamic eccentricity changes both vibration order and frequency. By applying it to the target model, 6-pole and 9-slot permanent magnet synchronous motors, the static eccentricity generates the vibration order of the original frequency, r = 2. In addition, the dynamic eccentricity generates vibration order, r = 2, not at the original frequency, but at the sideband frequency. It means that the static eccentricity increases the vibration of the original frequency and the dynamic eccentricity generates the sideband frequency while the vibration of the original frequency changes relatively little. The last proposal was verified with the finite element analysis and tests.

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.

Detection of static eccentricity fault in PSH induction motor by using external magnetic flux density

The objective of this paper is to make a clear and thorough investigation about the effectiveness of motor current signature analysis (MCSA) for detecting default indexes of static eccentricity in PSH induction motor. The obtained results using traditional technique (MCSA) are compared with spectrums of external magnetic flux density extracted from healthy and faulty motors. The work is carried out with transient finite element method (FEM) simulations considering motor operation under nominal mechanical load, the notching nature of stator and rotor and the non-linearity behavior of ferromagnetic material are taking into account.

Eccentricity fault detection in permanent magnet synchronous generators using stator voltage signature analysis

In this paper, an index is proposed for the detection of static eccentricity (SE), dynamic eccentricity (DE), and mixed eccentricity (ME) in a three-phase permanent magnet synchronous generator (PMSG). The proposed index is the amplitude of the sideband components with a particular frequency pattern which is extracted from the spectrum of the stator voltage. This index can be used in no load state prior to the loading of the generator which can cause damage in eccentricity conditions. Moreover, the proposed index works properly in loaded condition. Extraction of the proper indexes highly depends on precise computation of the necessary signals. Therefore, in order to fulfil the required precision, the time-stepping finite element method (TSFEM) is used to model the PMSG under eccentricity fault and to calculate the stator voltage as an appropriate signal for processing.

Motor Current Signal Analysis Based on a Matched Subspace Detector

Motor current signature analysis (MCSA) is a well-proven technique for electrical and mechanical faults detection in induction motors. The appearance of stator current components or increase of magnitude of some components at characteristic frequencies indicates a motor fault condition. In this paper, we propose a new MCSA fault detector based on a matched subspace technique. The proposed detector consists of three steps. First, the influence of the fundamental supply frequency is removed from the current signal using an interference cancellation technique based on oblique projection. Then, the fault-related frequency is estimated from the interference-free signal using the maximum likelihood principle. Finally, the fault detection is performed using a generalized likelihood ratio test. Simulation and experimental results illustrate the effectiveness of the proposed approach for eccentricity fault, bearing faults, and broken rotor bars detection.

An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

Detection of mixed eccentricity fault in doubly‐fed induction generator based on reactive power spectrum

Wide application of wind energy in the world towards reduction of global warming, have made the low cost maintenance of these turbines very important. Basically, mechanical faults such as gear-box faults in these turbines lead to a long down time and consequently heavy financial loss. Generally, these faults cause eccentricity in the generator air gap, so by its early detection the fault can be largely prevented. In this paper, eccentricity fault detection is studied in doubly-fed induction generator (DFIG) which is the most established generator in wind turbines and also is more prone to mechanical faults compared to other technologies. One of frequency components of reactive power is introduced as eccentricity fault index. As the reactive power is always evaluated in the control system, there is no need to include a new hardware for fault detection. Finite elements method is used to model the wound rotor induction machine (WRIM) which is coupled with closed-loop control system. Following the validation of the model in the healthy case experimentally, eccentricity under different operating conditions is included in the modeling. Finally, a simple procedure based on simple signal processing methods is introduced for eccentricity fault diagnosis considering the operating conditions of the wind turbine.

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 dealing with the topic of fault diagnosis in multi-phase PMa-SynRMs, and in particular, those focused on detecting eccentricity faults. An analysis of the spectral components of the line currents and the ZSVC allows the development of 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 an 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 employed 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 for developing fault diagnosis strategies based on the acquisition and subsequent analysis and interpretation of the spectral content of the line currents and the ZSVC.

Static air-gap eccentricity fault diagnosis using rotor slot harmonics in line neutral voltage of three-phase squirrel cage induction motor

The mixed eccentricity fault detection in a squirrel cage induction motor has been thoroughly investigated. However, a few papers have been related to pure static eccentricity fault and the authors focused on the RSH harmonics presented in stator current. The main objective of this paper is to present an alternative method based on the analysis of line neutral voltage taking place between the supply and the stator neutrals in order to detect air-gap static eccentricity, and to highlight the classification of all RSH harmonics in line neutral voltage. The model of squirrel cage induction machine relies on the rotor geometry and winding layout. Such developed model is used to analyze the impact of the pure static air-gap eccentricity by predicting the related frequencies in the line neutral voltage spectrum. The results show that the line neutral voltage spectrum are more sensitive to the air-gap static eccentricity fault compared to stator current one. The theoretical analysis and simulated results are confirmed by experiments.

Detection of Inter-Turn and Dynamic Eccentricity Faults Using Stator Current Frequency Pattern in IPM-Type BLDC Motors

This paper propose a fault detection algorithm for stator inter-turn faults (SITFs), dynamic eccentricity faults (DEFs), and hybrid faults (a combination of SITF and DEF) in a permanent magnet (PM) brushless dc motor. We analyzed specific frequency patterns of the stator input current to diagnosis and distinguish the fault types. First, we developed a two-dimensional (2-D) finite element method (FEM) program using a system matrix, and then we confirmed additional specific frequency patterns of the input current by a fast Fourier transform. Finally, specific frequency patterns for each fault type were verified by experimental results.

Detection of Static Eccentricity Fault in Saturated Induction Motors by Air-Gap Magnetic Flux Signature Analysis Using Finite Element Method

Unfortunately, motor current signature analysis (MCSA) cannot detect the small degrees of the purely static eccentricity (SE) defects, while the air-gap magnetic flux signature analysis (FSA) is applied successfully. The simulation results are obtained by using time stepping finite elements (TSFE) method. In order to show the impact of magnetic saturation upon the diagnosis of SE fault, the analysis is carried out for saturated induction motors. The index signatures of static eccentricity fault around fundamental and PSHs are detected successfully for saturated motor.

An Experimental Design for Static Eccentricity Detection in Synchronous Machines Using a Cramér–Rao Lower Bound Technique

Detection of a static eccentricity fault in rotating electrical machines is possible through several measurement techniques, such as shaft voltages and flux probes. A predictive maintenance approach typically requires that the condition monitoring technique is online, accurate, and able to detect incipient faults. This paper presents a study of the optimal measurement modality that leads to a minimal identification error of the static eccentricity in synchronous machines. The Cramér-Rao lower bound technique is implemented by taking into account both measurement and model uncertainties. Numerical results are obtained using a two-dimensional finite element model and is experimentally validated on a synchronous two-pole generator. Results indicate that shaft voltage measurements are better suited to the detection of static eccentricity.

An Online Method for Static Eccentricity Fault Detection in Axial Flux Machines

This paper investigates a novel online method for static eccentricity (SE) fault detection of single-stator-single-rotor axial flux permanent-magnet (AFPM) machines. The method allows for both estimating the SE factor and computing the minimum air-gap position. As direct flux measurements are expensive, the proposed method for fault detection is based on the measurement of the voltages of three search coils uniformly distributed in the air gap. Unlike the current spectrum-based fault detection methods on which the winding configuration has a considerable impact, the proposed method can be used for any type of AFPM machine independently on the winding layout. A simplified 2-D analytical approach is used. Moreover, a circuit-coupled 3-D finite-element method (FEM) was used to compute the induced voltages in the search coils and show the validity of the method through 20 eccentric scenarios. Moreover, an experimental setup was built to validate the analytical approach and to confirm the results achieved with the 3-D FEM. Several experimental measurements have been done. All measurements confirm the accuracy of the proposed method. It is also shown that the method yields accurate results under any load condition.

Application of the Goertzel’s algorithm in the airgap mixed eccentricity fault detection

In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT). However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel?s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor?s vibration signal analysis.

A Novel and Effective Method of Static Eccentricity Diagnosis in Three-Phase PSH Induction Motors

Eccentricity-related faults are very common in induction motors and that is the reason for the extensive and worldwide research on their prompt diagnosis during the past decades. Previous works have shown that traditional diagnostic methods cannot offer reliable results for principal slot harmonics (PSH) induction motors. Moreover, most works were focused in the detection of dynamic and mixed, rather than static eccentricity. This paper is focused on the detection of the static eccentricity fault and its severity in PSH induction motors. The proposed method is original and proves to be reliable for the static eccentricity fault detection, even when the severity of the fault is low. The work was carried out with both finite element method (FEM) simulations and experimental testing.

Comprehensive Detection of Eccentricity Fault in Switched Reluctance Machines Using High-Frequency Pulse Injection

This paper presents a comprehensive method for eccentricity fault diagnosis in switched reluctance machine (SRM) during offline and standstill modes. In this method, the fault signature is achieved by processing the differential currents resulted from injected high-frequency diagnostic pulses to the motor windings. For feasibility assessment of the proposed method, the correlation between differential current and eccentricity occurrence is analytically demonstrated. A 3-D transient finite-element method is utilized to analyze the proposal, and its results are validated by experimental tests on a prototype machine in the laboratory. According to the obtained results by experimental as well as numerical analysis, a pattern is introduced in order to detect fault presence. In this stage, an algorithm with two methods is proposed for the detection of fault location or faulty phase. Furthermore, the direction of fault is recognized by a simple comparative technique. Next, a normalized indicator is proposed in order to estimate the eccentricity fault severity as well as its occurrence. This indicator is not dependent of the healthy motor information, which makes it reliable and applicable tool for all sizes of SRMs. Finally, a simple procedure based on achieved pattern and indicator is implemented to distinguish the static, dynamic, and mixed eccentricity in the SRM.

Static Eccentricity Fault Detection in Single-Stator–Single-Rotor Axial-Flux Permanent-Magnet Machines

This paper studies static eccentricity (SE) fault detection in axial-flux permanent-magnet (AFPM) machines using 3-D finite-element analysis. The use of numerical modeling makes it possible to precisely study the eccentricity fault detection in these types of machines. The simulations are validated using experimental measurements. To the best knowledge of the authors, SE fault detection in AFPMs has not been studied before. Hence, a new definition for the SE factor is presented in these types of machines. A motor with different degrees of rotor eccentricity is simulated, and the back electromotive force (EMF) of all coils of the stator is obtained. In addition, an appropriate criterion has been presented for the fault detection using the back EMF of the coils. This study indicates that the back EMF of the coils of the stator is a good criterion for eccentricity fault detection. It is observed that the unbalanced back EMF suggests a method for the indirect measurement of eccentricity that could be carried out during manufacturing and assembling processes or maintenance operation.