Analysis of Ball Bearing Defects in Synchronous Machines using Electrical Measurements

Rolling element bearings are used in most electrical machines, especially for small and medium size applications. Under non-ideal operating conditions, ball bearing condition degrades by fatigue, ambient vibration, misalignment, overloading, contamination, corrosion from water or chemicals, improper lubrication, shaft currents and residual stress left from the bearing manufacturing process. All of these conditions eventually lead to increased vibration and acoustic noise during machine operation which at some point in time results in unexpected bearing failure. Over the years, a great number of publications have been devoted to the detection of mechanical faults, including rolling element bearing defects and torsional defects, in electrical machines based on Electrical Signature Analysis (ESA). It has been observed that these faults can affect either the stator to rotor air-gap distribution or the running speed of the machine, which can be reflected in the signature of the electrical signals. However, the physical link between the mechanical degradation and the electrical signature is still not explained well. A multi-physics model is developed by joining the detailed mechanical model of a rotor bearing system and the electrical model of a synchronous machine in this research. This combined model is capable of describing the transmission of information originating from bearing faults and their impact on the variations of the measured electrical signals. The electrical machine model is developed based on winding function approach and its validity is demonstrated by a more accurate Finite Element Method (FEM) model. The mechanical model consists of a high fidelity rotor-bearing system with detailed nonlinear ball bearing model and a flexible finite element shaft model. It is validated using the housing vibration data collected from some experiments. Generalized roughness bearing anomalies are linked to load torque ripples and airgap variations, while being related to current signature by phase and amplitude modulation. Considering that the induced characteristic signatures are usually subtle broadband changes in the current spectra, these signatures are easily affected by input power quality variations, machine manufacturing imperfections and environmental noise. In this research, a new algorithm is proposed to isolate the influence of the external disturbances of power quality, machine manufacturing imperfections and environmental noise, and to improve the effectiveness of applying the ESA for generalized roughness bearing defects. The results show that the proposed method is effective in analyzing the generalized roughness bearing anomaly in synchronous machines. Furthermore, the electrical signatures are analyzed in a synchronous machine with bearing defects. The proposed fault detection method employs a Zoomed Fast Fourier Transform (ZFFT) and Principal Component Analysis (PCA) and it is also tested on the available experimental data. The results show that amplitude induced electrical harmonics are related to the level of vibration, and the electrical signatures are affected heavily by other variables, such as power quality and load fluctuation. The proposed method is shown to be effective on detecting generalized roughness bearing defects in synchronous machines

A Review of Modeling and Diagnostic Techniques for Eccentricity Fault in Electric Machines

Research on the modeling and fault diagnosis of rotor eccentricities has been conducted during the past two decades. A variety of diagnostic theories and methods have been proposed based on different mechanisms, and there are reviews following either one type of electric machines or one type of eccentricity. Nonetheless, the research routes of modeling and diagnosis are common, regardless of machine or eccentricity types. This article tends to review all the possible modeling and diagnostic approaches for all common types of electric machines with eccentricities and provide suggestions on future research roadmap. The paper indicates that a reliable low-cost non-intrusive real-time online visualized diagnostic method is the trend. Observer-based diagnostic strategies are thought promising for the continued research

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

In-wheel motor vibration control for distributed-driven electric vehicles:A review

Efficient, safe, and comfortable electric vehicles (EVs) are essential for the creation of a sustainable transport system. Distributed-driven EVs, which often use in-wheel motors (IWMs), have many benefits with respect to size (compactness), controllability, and efficiency. However, the vibration of IWMs is a particularly important factor for both passengers and drivers, and it is therefore crucial for a successful commercialization of distributed-driven EVs. This paper provides a comprehensive literature review and state-of-the-art vibration-source-analysis and -mitigation methods in IWMs. First, selection criteria are given for IWMs, and a multidimensional comparison for several motor types is provided. The IWM vibration sources are then divided into internally-, and externally-induced vibration sources and discussed in detail. Next, vibration reduction methods, which include motor-structure optimization, motor controller, and additional control-components, are reviewed. Emerging research trends and an outlook for future improvement aims are summarized at the end of the paper. This paper can provide useful information for researchers, who are interested in the application and vibration mitigation of IWMs or similar topics

NOVEL METHODS FOR PERMANENT MAGNET DEMAGNETIZATION DETECTION IN PERMANENT MAGNET SYNCHRONOUS MACHINES

Monitoring and detecting PM flux linkage is important to maintain a stable permanent magnet synchronous motor (PMSM) operation. The key problems that need to be solved at this stage are to: 1) establish a demagnetization magnetic flux model that takes into account the influence of various nonlinear and complex factors to reveal the demagnetization mechanism; 2) explore the relationship between different factors and demagnetizing magnetic field, to detect the demagnetization in the early stage; and 3) propose post-demagnetization measures. This thesis investigates permanent magnet (PM) demagnetization detection for PMSM machines to achieve high-performance and reliable machine drive for practical industrial and consumer applications. In this thesis, theoretical analysis, numerical calculation as well as experimental investigations are carried out to systematically study the demagnetization detection mechanism and post-demagnetization measures for permanent magnet synchronous motors. At first a flux based acoustic noise model is proposed to analyze online PM demagnetization detection by using a back propagation neural network (BPNN) with acoustic noise data. In this method, the PM demagnetization is detected by means of comparing the measured acoustic signal of PMSM with an acoustic signal library of seven acoustical indicators. Then torque ripple is chosen for online PM demagnetization diagnosis by using continuous wavelet transforms (CWT) and Grey System Theory (GST). This model is able to reveal the relationship between torque variation and PM electromagnetic interferences. After demagnetization being detected, a current regulation strategy is proposed to minimize the torque ripples induced by PM demagnetization. Next, in order to compare the demagnetization detection accuracy, different data mining techniques, Vold-Kalman filtering order tracking (VKF-OT) and dynamic Bayesian network (DBN) based detection approach is applied to real-time PM flux monitoring through torque ripple again. VKF-OT is introduced to track the order of torque ripple of PMSM running in transient state. Lastly, the combination of acoustic noise and torque is investigated for demagnetization detection by using multi-sensor information fusion to improve the system redundancy and accuracy. Bayesian network based multi-sensor information fusion is then proposed to detect the demagnetization ratio from the extracted features. During the analysis of demagnetization detection methods, the proposed PM detection approaches both form torque ripple and acoustic noise are extensively evaluated on a laboratory PM machine drive system under different speeds, load conditions, and temperatures

Simplified Damper Cage Circuital Model and Fast Analytical–Numerical Approach for the Analysis of Synchronous Generators

The long and enduring history of utilization of the wound-field synchronous generator in a large number of applications makes it one of the most known and consolidated electrical machine technologies. Thus, its design, modeling, and analysis processes have been widely exploited and implemented through various and different methods, including the equivalent circuit approach. When a damper cage is embedded within the rotor of the synchronous generator, its theoretical analysis becomes quite complicated. Thus, today numerical tools are being used. In this paper, an alternative way of modeling symmetric damper cages of salient-pole synchronous generators is presented. The proposed approach is embedded in the circuital model of the generator. A hybrid analytical-numerical model is implemented, permitting to accurately predict the voltage waveforms of the generator with excellent accuracy, however, at a lower cost of computational resources than the pure numerical method. A case study of an off-the-shelf 400 kVA machine is considered to develop and validate the proposed technique. The results are compared with the corresponding finite-element and experimental evaluations for validation purposes

New synchronous machine rotor design for easy insertion of excitation coils based on surrogate optimisation

The thesis reviews the development of traditional synchronous machine design and point out one problem with the manufacture of wound rotor synchronous machines. Install and repair process of the rotor windings can be considered labor-costly and time-consuming in synchronous machine design. The conclusion indicates a new winding method would be helpful for not only the new machines but also for rewound machines. A new rotor design for the easy insertion and repair of the rotor windings is then introduced. This new asymmetrical rotor shows good potentials for reducing the maintenance and repair costs of synchronous machines, making it suitable for manufacturers within the mass production markets such as gen-sets, steam turbines, wind power generators. Simulation results from 2-D finite element analysis and experimental results from testing a 27.5 kVA prototype machine have verified the performance of the new rotor. The results show that the asymmetrical machine’s electromagnetic performance is worse than traditional design and need to be optimised. The shape of the rotor is then optimised based on novel surrogate method in order to achieve the lowest power loss under the maximum power output. This method combines surrogate optimistaion with finite element method. It significantly reduces the time cost of the optimization process and can be applied with very complicated geometry design of the rotor. The performance of the new rotor is examined in 2-D finite element software and validated by experiments. After optimisation, the efficiency of the new rotor can reach the same level of the traditional rotor in electromagnetic performance in addition to its easy insertion and repair feature

Electromagnetic modeling of large hydro electrical generators using 2D finite element method

With the ever increasing of the demand for electrical energy, the need for additional power has already become a reality in the energy supply market. In this context, increasing the power output of existing generators is considered as a promising and beneficial option. Unfortunately, the available methods today do not allow exploiting the full power potential of the existing generators with a precise evaluation of the impact of this increase on the residual lifetime. The challenge in uprating a large existing machine therefore is increasing the output power within the safety limits and without reducing the reliability of the system. One of the goals of Hydro-Québec is to develop new techniques which permit identification of units with potential for up rate. The understanding of the electromagnetic fields inside the generator and their implication in the losses is the first step to fulfil this goal. This thesis focuses on analyzing the electromagnetic field and establishing the magnetic core losses for different machine configurations and operating conditions. The electrical machine in question is a low-speed, salient poles synchronous generator. Initially, a literature review of the related subjects published in the last 20 years was investigated. Secondly, modelling analysis and simulation of large electrical machines using commercial software to compute the losses at the steady state was also done. Moreover, validation of this work and analysis is done using measurements of losses with emphasis on the core losses and magnetic flux density. The core loss matrix generated by FEM was also compared with the thermal calculation and measurements of the hotspots of the machine. The results from FEM simulation in comparison to the experimental measurements are presented for two machines (Manic 21 and Rapide-des-Quinze). The simulation and experimental results were in a good agreement

A Review of Techniques Used for Induction Machine Fault Modelling

[EN] Over the years, induction machines (IMs) have become key components in industry applications as mechanical power sources (working as motors) as well as electrical power sources (working as generators). Unexpected breakdowns in these components can lead to unscheduled down time and consequently to large economic losses. As breakdown of IMs for failure study is not economically feasible, several IM computer models under faulty conditions have been developed to investigate the characteristics of faulty machines and have allowed reducing the number of destructive tests. This paper provides a review of the available techniques for faulty IMs modelling. These models can be categorised as models based on electrical circuits, on magnetic circuits, models based on numerical methods and the recently proposed in the technical literature hybrid models or models based on finite element method (FEM) analytical techniques. A general description of each type of model is given with its main benefits and drawbacks in terms of accuracy, running times and ability to reproduce a given faultThis work was supported by the Spanish "Ministerio de Ciencia, Innovacion y Universidades (MCIU)", the "Agencia Estatal de Investigacion (AEI)" and the "Fondo Europeo de Desarrollo Regional (FEDER)" in the framework of the "Proyectos I+D+i-Retos Investigacion 2018", project reference RTI2018-102175-B-I00 (MCIU/AEI/FEDER, UE)Terrón-Santiago, C.; Martinez-Roman, J.; Puche-Panadero, R.; Sapena-Bano, A. (2021). A Review of Techniques Used for Induction Machine Fault Modelling. Sensors. 21(14):4855-4873. https://doi.org/10.3390/s21144855S48554873211

Electrical Signature Analysis of Synchronous Motors Under Some Mechanical Anomalies

Electrical Signature Analysis (ESA) has been introduced for some time to investigate the electrical anomalies of electric machines, especially for induction motors. More recently hints of using such an approach to analyze mechanical anomalies have appeared in the literature. Among them, some articles cover synchronous motors usually being employed to improve the power factor, drive green vehicles and reciprocating compressors or pumps with higher efficiency. Similarly with induction motors, the common mechanical anomalies of synchronous motor being analyzed using the ESA are air-gap eccentricity and single point bearing defects. However torsional effects, which are usually induced by torsional vibration of rotors and by generalized roughness bearing defects, have seldom been investigated using the ESA. This work presents an analytical method for ESA of rotor torsional vibration and an experimentally demonstrated approach for ESA of generalized roughness bearing defects. The torsional vibration of a shaft assembly usually induces rotor speed fluctuations resulting from the excitations in the electromagnetic (EM) or load torque. Actually, there is strong coupling within the system which is dynamically dependent on the interactions between the electromagnetic air-gap torque of the synchronous machine and the rotordynamics of the rotor shaft assembly. Typically this problem is solved as a one-way coupling by the unidirectional load transfer method, which is based on predetermined or assumed EM or load profile. It ignores the two-way interactions, especially during a start-up transient. In this work, a coupled equivalent circuit method is applied to reflect this coupling, and the simulation results show the significance of the proposed method by the practical case study of Electric Submersible Pump (ESP) system. The generalized roughness bearing anomaly is linked to load torque ripples which can cause speed oscillations, while being related to current signature by phase modulation. Considering that the induced characteristic signature is usually subtle broadband changes in the current spectrum, this signature is easily affected by input power quality variations, machine manufacturing imperfections and the interaction of both. A signal segmentation technique is introduced to isolate the influence of these disturbances and improve the effectiveness of applying the ESA for this kind of bearing defects. Furthermore, an improved experimental procedure is employed to closely resemble naturally occurring degradation of bearing, while isolating the influence of shaft currents on the signature of bearing defects during the experiments. The results show that the proposed method is effective in analyzing the generalized roughness bearing anomaly in synchronous motors