1- Introduction

2- Experimental rotor/AMB system

3- Strain measurement system

4- Strain measurement calibration

5- Dynamic results

6- Conclusions

References

Abstract

Active magnetic bearing systems provide contact-free rotor levitation, which allows near frictionless rotation and high rotational speeds when they operate normally. Under certain operational conditions, a transient fault, overload condition, or disturbance may occur. Touchdown bearings or bushings are therefore implemented in such systems to prevent contact between rotor and stator laminations. If the rotor makes contact with a touchdown bearing, the rotor dynamics may become transient or persistent in contact. Appropriate control strategies through the magnetic bearings to restore contact-free rotor operation may extend the life of touchdown bearings, and minimise operational downtime. To achieve this, an understanding of the contact dynamics is required, together with the relationship between contact and magnetic bearing forces. In this paper, rotor/touchdown bearing contact conditions are investigated experimentally using an active magnetic bearing system with a flexible rotor. Design methodology is presented for a measurement system capable of providing rotor/touchdown bearing contact related data, based on strain measurement. Strain induced contact signals are calibrated against applied magnetic bearing forces. The frequency dependent behaviour of the active magnetic bearing system is considered using evaluated force and phase measurements. The measurement data represent system identification for the potential of active magnetic bearing force-based contact control.

Introduction

The ability of Active Magnetic Bearings (AMBs) to provide contactless rotor levitation with vibration control has a number of benefits, including high-speed rotor operation, the elimination of the need for lubrication, long life and reliability, and energy efficiency due to the low friction losses. However, passive bearings are also used in AMB systems as Touchdown Bearings (TDBs) to prevent potentially damaging rotor/magnetic bearing stator contact from occurring. TDBs support the rotor while the AMB system is not operating, but also limit excursions of the rotor during operation, such as in cases of power loss, component failure, rotor mass loss, or other significant external disturbances. Such cases may cause rotor/TDB contact. Since TDBs are functional components of AMB systems, it is crucial to understand their influence on rotor dynamic behaviour in contact cases, in order to minimise potential damage. This is particularly important as TDB life and condition impacts directly on the reliability of AMB systems.

Introduction

BRB Detection Method Using Global Optimization Algorithm

Joint Algorithm Based on Particle Swarm Optimization and Trust Region

Detection Procedure of TR-MBPSO-Based Method and Simulation Analysis

Experimental Verification

Conclusions

References

Abstract

A precise detection of the fault feature parameter of motor current is a new research hotspot in the broken rotor bar (BRB) fault diagnosis of induction motors. Discrete Fourier transform (DFT) is the most popular technique in this feld, owing to low computation and easy realization. However, its accuracy is often limited by the data window length, spectral leakage, fence efect, etc. Therefore, a new detection method based on a global optimization algorithm is proposed. First, a BRB fault current model and a residual error function are designed to transform the fault parameter detection problem into a nonlinear least-square problem. Because this optimization problem has a great number of local optima and needs to be resolved rapidly and accurately, a joint algorithm (called TR-MBPSO) based on a modifed bare-bones particle swarm optimization (BPSO) and trust region (TR) is subsequently proposed. In the TR-MBPSO, a reinitialization strategy of inactive particle is introduced to the BPSO to enhance the swarm diversity and global search ability. Meanwhile, the TR is combined with the modifed BPSO to improve convergence speed and accuracy. It also includes a global convergence analysis, whose result proves that the TR-MBPSO can converge to the global optimum with the probability of 1. Both simulations and experiments are conducted, and the results indicate that the proposed detection method not only has high accuracy of parameter estimation with short-time data window, e.g., the magnitude and frequency precision of the fault-related components reaches 10−4 , but also overcomes the impacts of spectral leakage and non-integer-period sampling. The proposed research provides a new BRB detection method, which has enough precision to extract the parameters of the fault feature components.

Introduction

Induction motors are widely used in the industry, owing to many advantages such as simple construction, reliability and high efciency. Although such motors are considerably reliable and robust, they still sufer from internal machine faults caused by corrosive and dusty environments. One of the most common faults is a broken rotor bar (BRB), which accounts for approximately 10% of total induction motor faults [1]. Terefore, early BRB detection in induction motors is surely signifcant. When a broken bar occurs in the rotor, the geometry and magnetic fux of the motor are unbalanced. New sideband frequency components at (1±2s)f1 Hz will appear in the stator current, where s is the slip and f1 is the power supply frequency [2]. Tis implies that the BRB fault can be detected efciently by using the frequencies and amplitudes of (1±2s)f1 components. Tus, motor current signature analysis (MCSA), which is non-invasive, is the most widely used technique for BRB detection.

1. Introduction

2. Structure of motor for aero car

3. Optimization performance parameters of rotor based on Taguchi algorithm

4. Finite element experiment verification

5. Conclusion

References

Due to the long development cycle and high cost of aeronautical motor, the performance parameters of the rotor with Halbach array structure are optimized by Taguchi algorithm. The performance parameters mainly include the thickness of magnetic steel, the number of blocks per pole as well as magnetizing angle. The evaluation index of the optimized parameters is that the volume of the magnetic steel used is the smallest, the air gap magnetic density is the largest and its shape is closest to the sinusoidal. The experimental group is verified by finite element method. Finally, the rotor structure parameters satisfying the high power density and high air gap magnetic density of aeronautical motor are determined, which shortens the product development cycle and reduces cost of manufacture.

Introduction

The light weight of traditional motor is mainly focused on rotor, housing, and mount and stator. Solutions such as shaft opens pore will decrease strength of shaft; the housing, mount and stator achieve lightweight are depend on the way of developing new materials [2-4]; so the process of motor lightening is slow and the problem can not be solved fundamentally In this paper, for the rotor with Halbach array permanent magnet designed for aero car, Taguchi algorithm is proposed to optimize the height of Halbach array magnetic steel to reduce the volume of magnetic steel, and then reduce the curb weight of motor. At the same time, the number of Halbach arrays and magnetizing angle of magnetic steel are analysed. The optimal number of blocks per pole and the optimal magnetizing angle are determined to produce more larger and most uniform air gap flux density.

Repetitive control is an effective method to eliminate the effects of a periodic disturbance on a control system. In some applications the period is not known with sufficient accuracy, or the period may fluctuate sufficiently to seriously compromise performance. Second order repetitive control has been developed in response to this issue. Existing methods of analyzing stability for such systems are either very difficult to use, or excessively conservative sufficient conditions. A novel second order repetitive control is proposed here which achieves the behavior of second order but uses data from only one period in the past. This better meets the requirements for real time storage, but more importantly, it allows us to develop a stability criterion that is much less conservative. The experimental results demonstrate that the suppression effect can achieve a high level under frequency fluctuation with the proposed control method.

Introduction

A novel form of second order repetitive control (RC) is proposed in this paper, which can greatly facilitate the stability analysis. The motivation of the study originates from the urgent requirements of micro-vibration spacecraft. Spacecraft often suffer from vibrations produced by the rotating wheels used as attitude control actuators, i.e., reaction wheels or control moment gyros [1]. This degrades the performance of fine pointing equipment on board. Passive vibration isolation methods have limited performance, hence active vibration cancellation strategies are considered [2]. Laser communications between spacecrafts or with ground offer a different option of canceling the influence of spacecraft jitter by control methods applied to pan and tilt of the outgoing mirror [3] that cancels vibrations in the beam. The hardware demonstration of the proposed second order repetitive control approach, considers magnetically suspended rotor (MSR) performance, which can have disturbances of rotor mass imbalance and sensor runout. The objective is to reduce the vibrations at their source in the spacecraft, instead of at the sensor location of fine pointing equipment by vibration isolation.

This work proposes Isogeometric Analysis as an alternative to classical finite elements for simulating electric machines. Through the spline-based Isogeometric discretization it is possible to parametrize the circular arcs exactly, thereby avoiding any geometrical error in the representation of the air gap where a high accuracy is mandatory. To increase the generality of the method, and to allow rotation, the rotor and the stator computational domains are constructed independently as multipatch entities. The two subdomains are then coupled using harmonic basis functions at the interface which gives rise to a saddle-point problem. The properties of Isogeometric Analysis combined with harmonic stator–rotor coupling are presented. The results and performance of the new approach are compared to the ones for a classical finite element method using a permanent magnet synchronous machine as an example.

Introduction

Isogeometric Analysis (IGA) was first introduced in [1,2] and can be understood as a Finite Element Method (FEM) using a discrete function space that generalizes the classical polynomial one. IGA has already been applied in different fields such as, e.g., mechanical engineering [3] and fluid dynamics [4]. A more elaborated overview of relevant application fields can be found in [5]. In this paper, we propose the application of the concepts of IGA to electric machine simulation. According to IGA, the basis functions commonly used in Computer Aided Design (CAD) for geometry construction, i.e. B-Splines and Non-Uniform Rational B-splines (NURBS), are used as the basis for the solution spaces in combination with the classical FEM framework. IGA uses a global mapping from a reference domain to the computational domain and does not introduce a triangulation thereof. As a consequence, it is possible to represent CAD geometries exactly, even on the coarsest level of mesh refinement. The possibility to parametrize circular arcs (and other conic sections) without introducing geometrical errors is of particular interest for electric machine simulation since it guarantees an exact representation of the air gap, independently of the mesh resolution. Furthermore, thanks to the properties of Isogeometric basis functions, IGA solutions have a higher global regularity with respect to their FEM counterparts. The inter-element smoothness of the latter is typically restricted to C 0 . Moreover, IGA features a better accuracy with respect to the number of degrees of freedom compared to FEM [2,6,7]. Both advantages are of great importance for an accurate simulation of electric machines. For example, torques and forces are often calculated by the Maxwell’s stress tensor evaluated in the air gap, in which case the obtained results are very sensitive to the representation and discretization of the air gap [8]. This paper also tackles the problem of stator–rotor coupling which arises by our choice of IGA. The application of IGA for electric machine simulation is illustrated using a 2D magnetostatic formulation including the treatment of an angular displacement between stator and rotor. A further extension of the formulation to non-linear models [9], to time-harmonic [10] and transient formulations [11] and to the 3D case is straightforward. The structure of the paper is as follows. We first introduce the 2D model commonly used to describe electric machines. We discuss how IGA is used to discretize the model. Section 3 first presents a naive domain decomposition approach for stator–rotor coupling and then develops a Mortar coupling strategy based on harmonic functions that is in focus of this work. A simplified example is used to analyze the convergence and stability properties of the harmonic stator–rotor coupling. Finally, we apply the proposed method for simulating a permanent magnet synchronous machine (PMSM). The results are compared to a lowest order FEM.

A complex-valued Hopfield neural network (CHNN) is a multistate model of a Hopfield neural network. It has the disadvantage of low noise tolerance. Meanwhile, a symmetric CHNN (SCHNN) is a modification of a CHNN that improves noise tolerance. Furthermore, a rotor Hopfield neural network (RHNN) is an extension of a CHNN. It has twice the storage capacity of CHNNs and SCHNNs, and much better noise tolerance than CHNNs, although it requires twice many connection parameters. In this brief, we investigate the relations between CHNN, SCHNN, and RHNN; an RHNN is uniquely decomposed into a CHNN and SCHNN. In addition, the Hebbian learning rule for RHNNs is decomposed into those for CHNNs and SCHNNs.

INTRODUCTION

Acomplex-valued Hopfield neural network (CHNN) is a multistate model of a Hopfield neural network [1]–[3]. It is often applied to image storage [4], [5]. Several modifications and extensions of CHNN have been proposed [6]–[16]. A symmetric CHNN (SCHNN) is a modification of a CHNN [17]. An SCHNN has the same number of connection parameters and almost the same storage capacity as a CHNN. Since an SCHNN does not have rotational invariance, however, it has much better noise tolerance. A rotor Hopfield neural network (RHNN) is an extension of a CHNN [18]–[20]. Like SCHNN, RHNN does not have rotational invariance and improves noise tolerance significantly. In addition, RHNN has twice the storage capacity of CHNN, although twice many connection parameters are necessary [20]–[22]. RHNN has been applied to dynamic associative memories, such as chaotic associative memories that never recall rotated patterns [23], [24]. In this brief, the relations between CHNNs, SCHNNs, and RHNNs are studied. CHNNs and SCHNNs are organized based on complex numbers. Meanwhile, RHNNs are organized based on 2-D vectors and 2 × 2 matrices. RHNNs include both CHNNs and SCHNNs; CHNNs and SCHNNs can be represented by RHNNs. It is shown that an RHNN is uniquely decomposed into a CHNN and SCHNN. The decomposition matches a widely linear estimation [25]. However, there is a difference. In a widely linear estimation, the connections are one way. Meanwhile, in an RHNN, they are mutual. Widely linear estimation with complex numbers has been utilized in communications and adaptive filters [26]–[28]. In recent years, applications of widely linear estimation have been extended to quaternionic signal processing [29]. Moreover, the Hebbian learning rule for RHNNs is decomposed into those for CHNNs and SCHNNs. This brief provides a new perspective on the RHNN, and extends the strategy of learning algorithms.

Abstract

This paper addresses the application of rotor speed signal for the detection and diagnosis of ball bearing faults in rotating electrical machines. Many existing techniques for bearing fault diagnosis (BFD) rely on vibration signals or current signals. However, vibration- or current-based BFD techniques suffer from various challenges that must be addressed. As an alternative, this paper takes the initial step of investigating the efficiency of rotor speed monitoring for BFD. The bearing failure modes are reviewed and their effects on the rotor speed signal are described. Based on this analysis, a novel BFD technique, the rotor speed-based BFD (RSB-BFD) method under variable speed and constant load conditions, is proposed to provide a benefit in terms of cost and simplicity. The proposed RSB-BFD method exploits the absolute value-based principal component analysis (PCA), which improves the performance of classical PCA by using the absolute value of weights and the sum square error. The performance and effectiveness of the RSB-BFD method is demonstrated using an experimental setup with a set of realistic bearing faults in the outer race, inner race, and balls.

Introduction

FAULT diagnosis techniques are becoming more important as more engineering processes are automated, while the manpower needed to operate and supervise processes is reduced. Because rotating electrical machines (REMs) are at the heart of most engineering processes and are designed for tighter margins, there is a growing need for fault diagnosis for the sake of reliability. Different faults may occur in an REM, which can be classified as stator faults, rotor faults, static and dynamic eccentricities, and bearing faults [1]. Based on an IEEE motor reliability study for large motors above 200 hp [2]

Optimization of the ventilation system of the air-cooled turbo generator is crucial part of the development and leads to higher power output with the same dimensions. This goes hand by hand with the implementation of FEM software, which can be used for evaluations of the concepts and prototypes before production [1–4]. The alterations proposed in this article should cause reduction of pressure drop, better airflow distribution.

1.1 Turbo Generator Cooling System

Stator of the analyze turbo generator uses multi-compartment cooling system, see Fig. 1. The principle of this cooling system is based on over-pressure and under-pressure. The end-winding area is pressurized by axial ventilator. This pressure drives the airflow through three different branches. First branch is cooling stator. From the end-winding area, the air flows through transfer ducts to so called “cold” compartment from where it goes through the stator core to the airgap [5, 6]. Second branch represents airflow through rotor. Air flows under the end cap, where it is divided to cooled end-winding and rotor winding. Rotor winding is cooled via radial ducts, which are subject of the analysis. Last, the third branch is cooling first stator packets and join both stator and rotor branch in the air gap, from where it flows through stator core to the so called “hot” compartment and to the cooler.

1.2 Branch Effect

The velocity of the air which enters the rotor sub slot is very high, so the air cannot turn to the first radial ducts properly. Results is that there is non-uniform distribution of the airflow in radial ducts caused by air-vortexes, see Fig. 2. Those vortexes greatly reduce the usable cross-section. The branch effect can be calculated using empiric equation described in [7]. This equation gives us relative values of the airflow which can be multiplied by total airflow to get airflow in individual radial duct.

Reliable operation of critical power system components like transformers is essential for uninterrupted power supply to the consumer end whereas consistent functionality of induction motors ensure the smooth and uninterrupted industrial operations. However, performances of the critical components decline due to various environmental factors. Therefore, continuous assessment of these components is required to ensure their satisfactory performance. Equivalent circuit parameters characterize the behavior and performance of electrical machines. Hence estimation of equivalent circuit parameters can provide significant information about the condition and performance of the machine. Machine modeling is very important for state of the art modern ac drive systems, for example vector control of induction motor. In vector control of induction motors, determination of rotor flux linkage estimation is essential, which requires accurate estimation of motor equivalent circuit parameters The equivalent circuit parameters of electrical machines can be determined from the standard test procedures, as per IEEE guidelines [22]. However, being offline, the technique cannot be employed for the machines which are in operation. Besides, deviation of environmental conditions (like temperature, humidity etc.) can lead to the change of the equivalent circuit parameters. Therefore, the present research work is oriented towards assessing the condition of those components on-line.

1. مقدمه
با الزامات موجود درباره کاهش انتشار و بهبود اقتصاد سوخت، وسایل نقلیه الکتریکی و وسایل نقلیه الکتریکی هیبریدی (HEVها) توجهات بیشتری را معطوف بخود کرده اند، که انتظار بر این است در آنها قابلیت اطمینان بالا، چگالی قدرت زیاد، و قابلیت های اضافه بار بحد کافی باشد. همچنین، موتورهای مغناطیس دائم شار سوئیچینگ (FSPM) با توجه به چگالی های قدرت و گشتاور بالا علاقمندی های قابل ملاحظه ای را برای کاربردهای درایو با عملکرد بالا جذب کرده اند [2]-[9]. علاوه بر این، از آنجا که سیم پیچ های آرمیچر و آهنرباها هر دو در استاتور واقع هستند، یک ساختار ساده و قوی از روتور موجب می شود که ماشین های FSPM برای کاربردهای سرعت بالا مناسب باشد [10].
در این مقاله، یک موتور FSPM مدولار سه فازه تولید شده همراه با جریان بالا و ولتاژ پائین استفاده شده برای HEVها با استفاده از آنالیز اجرای محدود (FEA) طراحی می شود. مدل ابتدائی FEA بصورت تدریجی با در نظر گرفتن منحنی های B-H لمینیت تحت شرایط فرکانس های مختلف الکتریکی، دمای عملیاتی، اثر پایان سه-بعدی، و همچنین ملاحظه روتور خارج از مرکز بهبود می یابد. تاثیرات مربوطه در عملکردهای الکترومغناطیسی بطور عمیق، بخصوص برای نیروی ضد محرکه فاز، و گشتاورهای الکترومغناطیسی تحت عملیات مجاز بررسی می-شود. در مقایسه با مدل اولیه FEA، یک افت کلی 40 درصدی از گشتاور الکترومغناطیسی در مدل FEA بهبود یافته دیده می شود که بطور همزمان عوامل طراحی ذکر شده را در نظر می گیرد.