Electromagnetic vibrations estimation of an induction motor by nonlinear optimal filtering

A small, low-magnetic-noise nondestructive inspection (NDI) system that uses a high-Tc superconducting quantum interference device (SQUID) cooled by a coaxial pulse tube cryocooler (PTC) has been developed. The key components for realizing the compact, low-noise system developed in this study, include the following: a high-Tc SQUID gradiometer, the coaxial PTC, and a SQUID-mount stage separated from the cold head of the cryocooler. The high-Tc SQUID gradiometer contributes not only to stable system operation when subjected to the environmental noise without magnetic shielding, but also a decrease in magnetic noise caused by the mechanical vibration of the SQUID, which is transmitted from the cryocooler. By using the coaxial PTC, which was constructed of non-magnetic materials, both magnetic noise and the mechanical vibration are well suppressed compared to conventional two-axial PTCs. In addition, the coaxial PTC is designed to be compact (50 mm diameter, 400 mm height, and 4 kg weight) for practical use. The SQUID-mount stage separation contributes to stable operation by reducing the transmitted vibration to the SQUID, and thermal stability at the SQUID-mount stage. The magnetic flux noise spectrum of the cryo-cooled system was measured and compared with that of a liquid-nitrogen-cooled system using the same SQUID. From the comparison, no increase in magnetic noise due to the cryocooler was observed, although the magnetic flux noise level of the cryo-cooled system was dominated by SQUID operation noise, which was rather high, (i.e., around 100 μΦ0/Hz1/2 at 100 Hz). The relation between the mechanical vibration at the SQUID and magnetic noise is discussed.

A squirrel-cage induction motor is used in this paper for studying time harmonic current produced by frequency converter on account of the electromagnetic vibration. The order and amplitude of the radial electromagnetic force are obtained by the analytical calculation method and time-step finite element method. Combining 2D-fourier analysis, the frequency and amplitude of the force waves of the vibration response of induction motor are obtained, and the electromagnetic vibration response of the motor is calculated. Finally, the vibration response test was carried out on a prototype, electromagnetic vibration and the finite element simulation calculation results are in good agreement with the experimental results. The accuracy of the calculation result is verified in this paper.

LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis′s multi‐model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi‐model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF), which has been the standard nonlinear filter in past engineering applications.

A new method for a design of polynomial filters based on the Volterra series expansion is presented. The problem of nonlinear filter design is considered as a multi-objective problem and is solved by using an optimization approach. A theoretical background of the proposed method is stated. The obtained results allow one to design Pareto optimal filters in the presence of several conflicting criteria. In this case, the optimal nonlinear filter is characterized by a filter plane, which is tangent to a convex optimal decision function. The issue of reasonable choice of the design parameters defining the nonlinear filter performance is discussed. Examples of design, together with a performance comparison with other known nonlinear operators on simulated images, complete the article.

This study employs a consequent-pole rotor in an 18-slot/6-pole motor to reduce the use of permanent magnets (PMs). However, the adoption of a consequent-pole rotor may increase the torque ripple. In addition, the vibration performance may deteriorate because lower-order radial forces arise compared with a surface-mounted permanent magnet synchronous motor. Because these low-order radial forces result in large electromagnetic vibrations, the main flux density sources of these forces are identified. A harmonic flux barrier (HFB) is employed to reduce the lower-order radial forces by increasing the specific harmonics of the air-gap flux density. Furthermore, the HFB decreases the torque harmonics, which mitigates the torque ripple. The proposed consequent-pole PM motor (CPMM) with HFB (HFB-CPMM), as well as the conventional CPMM, are optimized using finite element analysis (FEA) to improve the electromagnetic vibration performance. In addition, the performance of the optimized HFB-CPMM (O-HFB-CPMM) is compared with that of the optimized conventional CPMM (O-CPMM). Consequently, O-HFB-CPMM is found to exhibit considerably lower PM usage, torque ripple, and radial force harmonics than the O-CPMM. Finally, the electromagnetic vibrations of both the optimized models are calculated using multi-physics FEA to validate the theoretical analysis and the proposed vibration reduction design. Air-gap flux density harmonics consequent pole permanent magnet (PM) motors radial force vibration reduction design.

A nanocrystalline shield for high precision co-magnetometer operated in spin-exchange relaxation-free regime

The theory of optimum nonlinear filters outlined in this paper is based on the consideration of a sequence of classes of nonlinear filters, designated as 𝔑1, 𝔑2, 𝔑3, …, such that each class in the sequence includes all the preceding classes and, furthermore, the class of linear filters is a subclass of every class in the sequence. A filter of class 𝔑m is described in terms of a characteristic function which involves m age variables and m values of the input time-function. The input-output relationship for a filter of class 𝔑m has the form of an m-fold integral of the characteristic function with respect to the m age variables. It is shown that the characteristic function of the optimum filter (in the least squares sense) within the class 𝔑m satisfies a linear integral equation of 2mth order. The optimization of filters of class 𝔑1 is treated in detail, and methods of approximate realization of such filters in the form of nonlinear delay line filters and power series filters are indicated. The results are extended to the case of nonstationary time series.

In-depth cross-coupling analysis in high-performance induction motor control

A Linear Method for the Design of Optimal Nonlinear Filters for Non-Gaussian Processes

This paper considers the nonlinear system filtering with packet dropouts. We assume that the packet arrived rate is known in advance but the sequence of packet dropouts is unknown. At first, we use the probability-weighted method to achieve a pseudo measurement sequence, and every pseudo measurement is the weighted value of the measurements acquired at the current time step and the prior time step. Some classical nonlinear filtering methods can be used via the pseudo measurement sequence and the dynamic equation of the system, and then the pseudo measurement unscented Kalman filter (PM_UKF) and the pseudo measurement particle filter (PM_PF) are given. This pseudo measurement sequence can be also used in the linear system, and its time complexity is lower than that of Sun's optimal filter at this time. Simulation results show the effectiveness of the proposed algorithms.

A training framework is developed in this paper to design optimal nonlinear filters for various signal and image processing tasks. The targeted families of nonlinear filters are the Boolean filters and stack filters. The main merit of this framework at the implementation level is perhaps the absence of constraining models, making it nearly universal in terms of application areas. We develop fast procedures to design optimal or close to optimal filters, based on some representative training set. Furthermore, the training framework shows explicitly the essential part of the initial specification and how it affects the resulting optimal solution. Symmetry constraints are imposed on the data and, consequently, on the resulting optimal solutions for improved performance and ease of implementation. The case study is dedicated to natural images. The properties of optimal Boolean and stack filters, when the desired signal in the training set is the image of a natural scene, are analyzed. Specifically, the effect of changing the desired signal (using various natural images) and the characteristics of the noise (the probability distribution function, the mean, and the variance) is analyzed. Elaborate experimental conditions were selected to investigate the robustness of the optimal solutions using a sensitivity measure computed on data sets. A remarkably low sensitivity and, consequently, a good generalization power of Boolean and stack filters are revealed. Boolean-based filters are thus shown to be not only suitable for image restoration but also robust, making it possible to build libraries of "optimal" filters, which are suitable for a set of applications.

The speed control of induction motors can be divided into two distinct strategies, depending on the type of dynamics that is required: scalar control (static control of the torque) and vector control (dynamic control of the torque) (Blaabjerg et al. 2005; Bose, 2000, 2006; Filote et al. 2009; Holtz, 2002; Leonhard, 1990; Umanand & Bhat, 1995; Vas, 1998). Since the couple and flux levels depend on the motor behavior to frequency and voltage applied to it, maintaining the flux constant is strongly required in scalar control (V/f control). Despite the simplicity and the low cost implementation of the control method, it still presents the disadvantage of poor torque dynamics. Vector control reassesses one of the advantages of direct current (dc) drives, which is the separation of speed and couple loops. According to its structure and to its own functioning principle, the dc drive is naturally field oriented, hence, the separation of the speed and current loops. In the case of vector controllers of induction motor, the magnitude and phase stator current are controlled in accordance with the flux vector. There are three vector control strategies according to the type of drive-controlled flux: stator flux, rotor flux and air gap flux. We can determine the magnitude and position of the rotor flux by using flux sensors (direct field-oriented control), estimators or observers (indirect field-oriented control) and by measuring some electrical and mechanical measurable states of electrical drives induction motor systems. When the rotor flux estimation is performed after measuring only the electrical measurable states (voltages and stator currents), in this case we have a sensorless vector control system. The implementation of the direct field-oriented control requires the measurement or calculation of the flux space vector (magnitude and position). The measurement of the air gap flux requires the use of some Hall sensors (Umanand & Bhat, 1995), which requires specially constructed induction motor. On one hand, they are very sensitive to temperature and mechanical vibrations. The flux signal is highly distorted by slot harmonics (Kreindler, 1994), whose spectrum and amplitude depend on the rotor speed (hence, the difficulty to be filtered). The implementation of the indirect field-oriented control requires the identification of rotor flux instantaneous position, and the calculus of stator current prescribed value in sensorless vector control system (Gadue et. al. 2009; Griva et al. 1997; Lascu et al. 2004). The

AZ91 Mg alloys are highly demanding in the automotive, aerospace, electric, and communication industries. However, there are some melting and casting problems associated with Mg alloys. The Peeling–Bedworth ratio of MgO is only 0.7. Hence, the oxidation of the metal is progressive and it requires protection against oxidation. Magnesium alloys are melted under a flux cover of KCl + MgCl2 which dissolves MgO. Before removal, the dross is usually thickened by the addition of CaF2. After dross removal, the exposed magnesium melt burns in contact with air. Hence, the exposed magnesium bath is protected by sprinkling sulfur powder which prevents magnesium oxidation. Alternatively, the melting may be carried out in an atmosphere of CO2 + 0.5 SF3. During pouring, sulfur powder is usually sprinkled on to the stream of metal. So, great care is required in synthesizing the Mg alloy. Due to the large freezing range, Mg–Al Alloys are subjected to the formation of coarse grained structure. Magnesium alloys are therefore treated for grain refinement. Microstructure refinement can either be done by the chemical method in which grains are refined by adding the grain refiners; or by imposing vibrations to the solidifying melt. Due to imposed vibrations, the dendrites are broken down and result in finer and equiaxed morphology. The vibrations can be imposed through three different ways: mechanical vibrations, electromagnetic vibrations, and ultrasonic vibrations. In mechanical vibrations, the mold is vibrated. There are two distinct views regarding the mechanism of mechanical vibrations: (i) cavitation effects and (ii) the effect of the fluid-flow phenomena. The mechanism of microstructure formation during electromagnetic vibration processing is also cavitation, from which the shock pressure is yielded and thus the growing dendrites fragmented into small pieces that provide an artificial source of effective nuclei for grain multiplication. During ultrasonic vibrations, the intensity of vibration soothes quickly as the distance from the transmitter increases. Consequently, the grain refinement is always limited near the area of the vibration source. Vibrations have a strong effect on microstructure and mechanical properties. The changes in properties remain consistent with fine uniform non-dendritic grains. In the present paper, the above issues are critically discussed along with the mechanism of grain refinement.

The electromagnetic vibration caused by electromagnetic force on the stator has threatened large hydro generators operating safely and stably. At the Zhexi hydropower station, the hydro generator was beset by electromagnetic vibration for a long time. Therefore, the paper provided a new method to help to find the vibration source and detect the hydro generator fault, through the combination of simulation and experiments. In this paper, the 3D stator pack structure model and the 2D hydro generator electromagnetic models under rotor eccentricity and rotor ellipse deformation conditions were built. Then, electromagnetism simulations were conducted to study the characteristics of the electromagnetic flux and electromagnetic force under different conditions by using the finite element method (FEM). Lastly, the vibration testing experiments and harmonic response simulations of stator frame were performed to present the characteristics of vibration distribution in frequency conditions. The simulation results were compared with the generator measured data to try to find out the main vibration source and guide the overhaul.

Introduction Energy harvesting is a process of producing energy or usable power from the environment. Among potential ambient energy harvesting sources, electromagnetic (EM) field offers the great promise for emerging power system applications. This is because EM energies are widely available around the current-carrying wires (busbars) that connect various power devices and equipment. Most previous works on EM energy harvesting were built upon AC transmission lines [1-5], whereas modern power systems are typically driven by renewable DC energy sources. In this work, a mechanically-driven, DC-based EM energy harvesting system is designed and implemented as a lab-scale prototype to ultimately power sensing devices in the power system. Key Results: The schematic diagram and the photograph image of the EM induction experimental setup are shown in Figures 1a) and 1b), respectively. The energy harvester consists of a high permeability (μ ~ 2300) ferrite toroidal coil (cross sectional area 760 mm2) that is placed below a DC conducting (copper) slab at a distance of 1 cm. According to the Faraday’s law of induction (Equation 1), the open circuit voltage is proportional to the time rate of change of the magnetic flux (dφ/dt). This work is sharply distinguished from other works because the time variant nature originates from the physical vibration without using the AC power source. As seen in the figure, the toroidal coil is directly attached to a vibrator, thus experiencing a light-to-moderate amount of vibration. Here, the copper slab emulates the busbar in the power system, and the vibrator represents a practical scenario where the energy harvester is exposed to mechanical, machinery, and other noise sources.Figure 2 plots the open circuit voltage (VOC) as a function of the number of coil turns (N) for the experimental setup shown in Fig. 1. VOC was measured using a multimeter between two terminals of the coil for the maximum current of 3 A applied to the copper slab. As expected, a linear trend of VOC vs. N was observed with the VOC value as high as 51.4 mV for the case of 2,500 turns. Importantly, VOC is scalable to the value that is sufficiently high to drive most modern sensing devices because VOC is proportional to current (I). It is common that more than 100 A flows in the busbar of the power system, which escalates VOC to more than 1.7 V. The idea of increasing VOC by increasing current is confirmed in Figure 3; we repeated the experiments by lowering the current value in the copper slab, and obtained the linear trend line. Thus, both results shown in Figures 2 and 3 indicate a strong correlation of our energy harvester prototype with the EM theory. The maximum VOC value we obtained (51.4 mV) is separately shown in Figure 4 as a photograph image of the multimeter reading.In Table 1, we estimated the VOC values that can be readily achievable in the power system that affords the busbar current of 300 A and/or the 10,000 coil turns. For example, as compared with a previous work [3] with VOC of 1.4 V for 30 A (AC), this work features VOC of about 2 V with the 30 A DC power source. Significance: This work demonstrates the possibility of newly developing an mechano-electromagnetic energy harvester for modern power systems. Taking full advantage of EM energies and vibration present in the power system, the proposed DC-sourced energy harvesting scheme can greatly facilitate development and adoption of various sensing/monitoring/diagnosis device technologies. This is because these devices will not require separate batteries or power sources; they will be easily powered using the electromagnetic energy and mechanical vibration.