Multiple Rotor Research Articles

STATIC ECCENTRICITY FAULT DETECTION METHOD FOR ELECTRICAL ROTATING MACHINES BASED ON THE MAGNETIC FIELD ANALYSIS IN THE AIR GAP BY MEASURING COILS

Electrical rotating machines have a great economic significance as they enable conversion of energy between mechanical and electrical state. Reliability and operation safety of these machines can be greatly improved by implementation of continuous condition monitoring and supervisory systems. Especially important feature of such systems is the ability of early fault detection. For this reason, several methods for detection and diagnosis of the machine faults have been developed and designed. As fault detection methods can largely differ in the types of detectable faults, machine adoptability and price of the system, a novel method was developed that can be used for cost-effective detection of various faults of electrical machine. Machine fault detection technique presented in this paper is based on the measurement of magnetic field in the air gap. Numerous studies have proven that crucial information about the machine condition can be determined based on measurement and analysis of the magnetic field in the air gap. It has also been confirmed that analysis of the air gap magnetic field can be used to detect, diagnose and recognize various electrical faults in their very early stage. Proposed method of positioning and installation of the measuring coils on ferromagnetic core parts within the air gap region of the machine enables differentiation of various faults. Furthermore, different faults can be detected if measuring coils are placed on the stator teeth then when placed on the rotor side. The paper presents method on how to analyse and process the measured voltages acquired from measuring coils placed within the machine, especially in the case of rotor static eccentricity detection. The methodology is explained by means of finite element method (FEM) calculations and verified by measurements that were performed on the induction machine. FEM calculation model was used to predict measurement coil output of the induction motor for healthy and various faulty states (at different amounts of static eccentricity). These results were then confirmed by measurements performed in the laboratory on the induction traction motor that was specially modified to enable measurements of faulty operation states of the machine. Measurements comprised of several machine fault conditions broken one rotor bar, broken multiple rotor bars, broken rotor end ring and various levels of rotor static eccentricity.
 Other methods used for faults detection are primarily based on the monitoring of quantities such as current and vibration and their harmonic analysis. This new system is based on the tracing the changes of induced voltage of the measuring coils installed on the stator teeth. Faults can be detected and differentiated based on RMS value of these voltages and the number of voltage spikes of voltage waveform i.e. without the need of harmonic analyses. If these coils are installed on the rotor it is possible to detect the stator winding faults in a similar manner.

A simple method for modelling fatigue spectra of small wind turbine blades

AbstractSmall‐scale wind turbines have market opportunities in distributed energy generation applications but face future challenges in remaining cost competitive compared with solar photovoltaic systems. High unit costs can be attributed to design conservatism when calculating fatigue loads of key structural components such as the blades. In this study, we use the aeroelastic software FAST to highlight limitations of the International Electrotechnical Commission 61400‐2:2013 small wind turbine design standard for calculating fatigue life using the simplified load model. We present a modified method for calculating the fatigue spectra of small wind turbine blades. An advantage of this method is that it does not require complex aeroelastic simulations or field measurements. This modified method is intended to be implemented early in the blade design stage, such as during rotor optimization simulations, allowing for multiple rotor configurations to be rapidly compared.

Rotor Blades Micro-Doppler Feature Analysis and Extraction of Small Unmanned Rotorcraft

In this article, the micro-Doppler feature analysis and extraction of small unmanned rotorcraft (SUR) is considered. To be specific, the radar returns from the rotor blades are first modeled as sinusoidal frequency-modulated (SFM) signals. Then, the Gabor transform is utilized to obtain the time-frequency distribution (TFD). In order to solve the problem of limited TF analysis resolutions, high carrier frequency of radar is employed for the sake of separating different sinusoidal curves from TFD. After that, the Hough-Radon transform (HRT) is introduced to detect the sinusoidal curves from the TFD. Finally, based on the relationship between the SFM signal and the rotating blade, the micro-Doppler parameters which can reflect the threat level of the SUR to a large extend are estimated. Compared with other existing methods, the proposed method presents the relationships between the carrier frequency and the rotating blade parameters and it can be employed to extract the micro-Doppler feature of SUR with multiple rotor hubs. Simulation results demonstrate the effectiveness of the proposed micro-Doppler feature extraction method.

Diagnosis of Multiple Rotor Bar Faults of Squirrel Cage Induction Motor (SCIM) Using Rational Dilation Wavelet Transforms

Vibration is the vital feature of the motor to diagnose various faults. The existing methods have many limitations. This work proposes a non-invasive Software Phase Locked Loop (SPLL) technique to diagnose the multiple rotor faults. A high-frequency (10.525GHz) microwave signal is projected on the motor and the reflected signal is captured by the handheld ultra-wide band (UWB) radar. Hardware filter is replaced by a software phase locked loop filter to remove high-frequency noise content in the signal. The output of the SPLL is analysed with Rational Dilation Wavelet Transforms (RDWT) and compared the change in the signal energy of the wavelet sub-band 6 for the multiple rotor bar faults and sub-bands 6 and 7 for the combination of rotor bar and bearing faults, respectively. The signal energy at sub-band 6 increased from 2.19% without fault to 3.99%, 6.03% and 13.66% with an increase in the number of rotor bars with faults. The variation of the experimental values of the signal energy for rotor bar faults compared with the theoretical values found that the error is reduced and accuracy is increased with the number of faults. For simultaneous rotor bar and bearing faults, the signal energy at sub-bands 6 and 7 also increases. The proposed SPLL-based method that is able to diagnose the individual faults and combination of the faults and has advantages such as simple, cost-effective and non-invasive technique compared with the existing methods.

A Fault Diagnosis Model Based On Full Vector Spectrum And Feature Engineering

Aiming at the problem of how to quickly and accurately diagnose different types of rotating machinery faults, this paper starts with the combination of full-vector spectrum theory and feature engineering. A model of rotor imbalance faults diagnosis and identifying is constructed in the process of dealing with the data sets of multiple rotor imbalance fault. The result shows that this fault diagnosis model combined with the full vector spectrum theory and feature engineering can be used to correctly distinguish the faults of the equipment and accurately identify the types of the unbalanced faults.

Balancing optimization of a multiple speeds flexible rotor

The paper describes a method to perform the dynamic balancing of multiple speeds flexible rotors. The method is integrated with a dual-objective optimization method (DOM) to overcome the shortcomings that classical least squares influence coefficient method (LSM) may induce by generating excessive residual vibrations at specific rotor speeds when a flexible rotor is dynamically balanced. The technique here described involves two consecutive optimization steps. During the first step an optimal correction weight of the parameters population is identified by using a genetic algorithm (GA) applied to an objective function made from the sum of the squares of the residual vibrations. This first optimization step is performed multiple times to obtain a set of optimized correction weights. A second optimization process is then performed by minimizing the maximum value of the residual vibration of the rotor. Each correction weight belonging to the first optimization set is embedded into an equation that represents the residual vibration to obtain the final optimal correction weight. The validity of the proposed method is verified by simulations and experiments related to a double-disc rotor-bearing system. The results show the DOM provides a more effective balancing strategy than the one obtained from using GA and classical LSM.

CFD analysis of the effects of multiple semicircular blades on Savonius wind turbine performance

The goal of this work is to simulate and improve the efficiency of an innovative multiple semicircular-bladed Savonius wind turbine, which is identified as belonging to the vertical axis wind turbine (VAWT) category. It is characterized as a low speed turbine that is simpler and cheaper to build than traditional turbines. This makes it appropriate for generating mechanical energy in lower wind speed regions, and it can be coupled with solar panels in urban agglomerations. The objective of this paper is to compare the aerodynamic characteristics and power efficiency of four different geometries of the Savonius wind turbine (two-conventional and two-modified rotors) in order to estimate the most efficient design. The proposed Savonius design comprises multiple semicircular blades added to conventional two- and three-bladed Savonius rotor configurations. The comparison of the efficiency in terms of the torque coefficient (C T ) and power coefficient (C P ) of the new system configurations with the conventional ones finds that the multiple semicircular two-bladed Savonius rotor is more efficient than others. The numerical simulation of the conventional Savonius rotor is developed and validated against experimental and numerical data derived from a literature review. The choice of turbulence model and local or global mesh refinement play essential roles in the accuracy of the numerical simulation results. In this work, we adopted a Shear Stress Transport (SST) model for modelling turbulence, which incorporates the near wall fluctuation capturing capability of the k-w model, and the robust k-ei€ model for modelling the whole numerical domain. An average improvement in the power coefficient of 8.43% for different tip speed ratios (TSRs) is observed for the new configuration compared with the others.

Quasi-Static Torque Profile Expressions for Magnetic Resonance-Based Remote Actuation

Resonant wireless power transfer has been employed to transfer electrical power from a transmitter to a receiver coil over an air gap and to remotely charge consumer devices. In this paper, the receiver coil is replaced by a stator–rotor topology, enabling magnetic resonance based motoring over substantial air gaps. The principles of resonant wireless power transfer are used to induce currents in a strongly coupled magnetic resonance system. This results in its turn-in torque, which is applied on the rotor body, allowing for remote actuation. We propose a voltage or current controlled magnetic resonance motoring topology, for which we derive expressions for the generated torque depending on the rotor angle. Furthermore, torque profile expressions are derived for motoring systems with multiple stator and/or rotor coils. Finally, an experimental setup is built to validate the obtained torque expressions. Using the validated expressions, we present a sensitivity analysis of the key system parameters with respect to the torque profile. The presented torque profile expressions enable further topology exploration and optimization of magnetic resonance based motoring systems.

THE LOW ROTATION 1 PHASE AC GENERATOR USING MULTIPLE STATOR AND ROTOR METHOD IN THE FLOATING-HYDRO POWER PLANT

Abstract — Electrical energy is the most vital necessity in daily human’s life. The need of electrical energy has been continuously increasing along with the industry and society development. Indonesia is a tropical country with loads of energy sources which one of them is the new renewable energy sources. There are still many unexploited river flows that possess potentials as energy sources. The Floating-Hydro power plant is one of portable power plants harnessing the river flows as the energy source. In this study, the Low Rotation 1 Phase AC Generator Using Multiple Stator and Rotor Method in the Floating-Hydro Power Plant was designed. This generator consisted of several stators and rotors. The stator was strung together using the enamel wire. As in accordance to the design outcome, the number of stator windings was 364 per coil, the space between windings was 4cm, and the stator diameter was 25cm. Meanwhile, the rotor consisted of Neodymium (NdFeB) type permanent magnet which was going to be induced into the stator. Every rotor consisted of 10 pieces of permanent magnet with a space between magnets was 2cm. The experiment result, which was performed on the 1 phase axial generator using 2 stators and 3 rotors with loads in the form of 3 pieces of 35W 12VAC lamps, generated voltages of 2,1 VAC with currents of 0,03A at the low speed of 100rpm. Meanwhile, at the speed of 1200rpm, it generated voltages of 10,68VAC with currents of 0,23A. DOI : https://doi.org/10.26905/jeemecs.v2i2.3205

Predicting the stochastic aerodynamic loads on blades of two yawed downwind hawts in uncontrolled conditions using a bem algorithm

Accurate predictions of the cycle-to-cycle variations in aerodynamic loads on wind turbine blades are important for estimating the life cycle costs of new wind power plants. Physical modelling of wind turbine systems is usually based on the average values of the aerodynamic parameters in the design process which would eliminate some important physical phenomena associated with the unsteady flows over the rotating blades. This paper presents a new algorithm implemented in a Blade Element Momentum (BEM) model to predict the cycle-to-cycle variations in the aerodynamic loads over multiple rotor rotations (cycles) for yawed rotors operating in natural flow conditions. In this approach, simulation theory developed by the Pacific Northwest Laboratories (PNL) is used to generate input turbulent wind speed time series on the whole rotor disc of two three-bladed downwind horizontal axis wind turbine (NREL Phase II and III) rotors. The unsteady influences of the dynamic stall kinematics and tower shadow are also considered in the current algorithm along with the phenomenon of stall delay. Predictions from the unsteady BEM model are compared to measured results and conclusions are drawn about the ability of the model to accurately simulate blade response to turbulence.

Coreless and Conventional Axial Flux Permanent Magnet Motors for Solar Cars

Axial flux permanent magnet (AFPM) motors are suitable options for solar-powered vehicles due to their compact structure and high torque density. Furthermore, certain types of AFPM machines may be configured without stator cores, which eliminates associated losses and cogging torque and simplifies the manufacturing and assembly. This paper examines two machine designs for use in the solar-powered vehicle of the challenger class—a single rotor, single stator conventional AFPM machine, and a coreless AFPM machine with multiple stator and rotor disks. The response surface methodology (RSM) is utilized for the systematic comparison of the conventional and coreless topologies and to select the optimum designs among several hundreds of candidates. Designs with minimum losses and mass producing required torque with larger air-gap are favored. The performance of the selected designs has been studied via three-dimensional finite element analysis (FEA). The FEA parametric modeling methodology is validated by measurements on three AFPM machines of the conventional and coreless type.

Numerical simulation and experimental testing of dynamic stiffness of angular contact ball bearing

Angular contact ball bearings are widely used in the multiple rotor system, such as gear box, machine tool spindle, and aero-engine rotors. The support stiffness is very important to the vibration of shafting. In order to obtain the dynamic stiffness, a numerical simulation method for dynamic stiffness of angular contact ball bearings is presented. By means of LS-DYNA software, the displacement and stress curves of the bearing’s different components are obtained successfully, and then, the dynamic stiffness of bearing under certain working conditions also can be calculated. The maximum envelope radius of the inner ring of the measured bearing can be taken as the relative displacement change value of the inner and outer rings of the bearing. To obtain the dynamic stiffness, the test strategy for dynamic stiffness of the angular contact ball bearings is introduced. The experimental results show that the equivalent dynamic stiffness increases with the increase in the preload of measured bearing under certain conditions. The simulation result coincides with the experiments well. The research work can provide the basis for the design and dynamics analysis of the bearing rotor system and have important engineering significance to improve the service performance of angular contact ball bearings.

Novel approach using Hilbert Transform for multiple broken rotor bars fault location detection for three phase induction motor

This paper presents a new approach to detect the location of multiple broken rotor bars (MBRBs) in induction motor (IM) drive, running under no load and full load conditions using direct in and variable frequency drives. This technique is based on earlier work of location detection of one broken rotor bar. The techniques are tested for various fault severity levels so the detection of the exact location of the fault at early stage helps to reach sufficient time maintenance. In this paper, the authors used Hilbert Transform to extract the fault signature from the stator current envelope which is the low frequency component. Then statistical analysis is applied which produce a formula that is used to get the exact location of the fault in IM rotor.

Multiple Rotors Hovering Near an Upper or a Side Wall

The influence of walls on the performance of multiple rotor type drones is numerically simulated. With the current wide-spread applications of autonomously flyable UAVs, there are potential needs to use the drones for inspections and observation near various structures, such as buildings and bridges. The flow fields around multiple rotors are influenced significantly by the existence of an upper or a side wall, so that the thrust, required torque, and other forces and moments are changed. It is found that when a rotor approaches an upper wall, as the distance between the rotor and the upper wall is less than a diameter of the rotor, the thrust suddenly increases, which causes the rotors to collide with the upper wall. When an isolated rotor is operated near a side wall, the thrust decreases and a rolling moment appears to tilt the rotor toward the wall as the distance becomes shorter. For a multiple rotor drone near a side wall, the rotors have different distances from the wall, which causes the whole aircraft tilts toward the wall. From the perspective of safety operations, the multi-rotor drone should be kept away from both the upper wall and the side wall at a distance of at least 1.5 times of the rotor diameter to prevent unexpected motions of the aircraft caused by the wall during hovering flight.

Multi-speed sedimentation velocity implementation in UltraScan-III

A framework for the global analysis of multi-speed analytical ultracentrifugation sedimentation velocity experiments is presented. We discuss extensions to the adaptive space-time finite element fitting methods implemented in UltraScan-III to model sedimentation velocity experiments where a single run is performed at multiple rotor speeds, and describe extensions in the optimization routines used for fitting experimental data collected at arbitrary multi-speed profiles. Our implementation considers factors such as speed dependent rotor stretching, the resulting radial shifting of the finite element solution's boundary conditions, and changes in the associated time-invariant noise. We also address the calculation of acceleration rates and acceleration zones from existing radial acceleration and time records, as well as utilization of the time state object available at high temporal resolution from the new Beckman Optima AUC instrument. Analysis methods in UltraScan-III support unconstrained models that extract reliable information for both the sedimentation and the diffusion coefficients. These methods do not rely on any assumptions and allow for arbitrary variations in both sedimentation and diffusion transport. We have adapted these routines for the multi-speed case, and developed optimized and general grid based fitting methods to handle changes in the information content of the simulation matrix for different speed steps. New graphical simulation tools are presented that assist the investigator to estimate suitable grid metrics and evaluate information content based on edit profiles for individual experiments.

A detailed one-dimensional model to predict the unsteady behavior of turbocharger turbines for internal combustion engine applications

This article describes an investigation of the unsteady behavior of turbocharger turbines by one-dimensional modeling and experimental analysis. A one-dimensional model has been developed to predict the performance of a vaneless radial-inflow turbine submitted to unsteady flow conditions. Different from other approaches proposed in the literature, the turbine has been simulated by separating the effects of casing and rotor on the unsteady flow and by modeling the multiple rotor entries from the volute. This is a simple and effective way to represent the turbine volute by a network of one-dimensional pipes, in order to capture the mass storage effect due to the system volume, as well as the circumferential variation of fluid dynamic conditions along the volute, responsible for variable admittance of mass into the rotor through blade passages. The method developed is described, and the accuracy of the one-dimensional model is shown by comparing predicted results with measured data, achieved on a test rig dedicated to the investigation of automotive turbochargers. The validation of the code is presented and an analysis of the flow unsteadiness, based on a variety of parameters, is proposed.

A Single-Channel Blind Source Separation Technique Based on AMGMF and AFEEMD for the Rotor System

To improve the accuracy of the diagnosis of the composite failure of the rotor system under underdetermined conditions, a single-channel blind source separation method based on an adaptive multiscale generalized morphology filter (AMGMF) and an adaptive fast ensemble empirical mode decomposition (AFEEMD) algorithm is proposed. First, AMGMF is used to filter out the background noise in the signal and enhance the signal-to-noise ratio (SNR), and then, the filtered signal is decomposed by the AFEEMD algorithm to improve the accuracy of signal decomposition and reduce computation time. Second, the singular value decomposition-based method is used to estimate the number of source signals, and the main components highly correlated with the observed signal are selected according to the number of source signals. Finally, the effective separation of source signals is achieved by the fast independent component analysis (FastICA) algorithm. Simulation tests and multiple rotor fault signals are used to demonstrate the feasibility and effectiveness of the proposed method. Experimental results show that the proposed method has better separation performance than the existing EEMD-PCA-FastICA method.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

A smart diagnosis system based on automatic recognition of multiple rotor faults

Diagnosing rotor faults is considered as one of the most vital tools for health maintenance of rotating machinery. In this work, a smart diagnosis system based on automatic recognition of multiple rotor faults is developed. As rotor faults are comparatively complicated, the reasoning mechanism of composite nesting probability reasoning network knowledge expression and multiple reasoning methods are adopted. Besides, methods such as fuzzy pattern recognition and image analysis are also applied to conduct automatic recognition of fault symptoms like rotor vibration spectrum, shaft centerline orbit, and transient features. Also, this article attempted to propose artificial neuron network study and diagnosis methods on the basis of fractal features of faults, set up a smart diagnosis system based on automatic recognition of multiple rotor faults, and verify the feasibility of system diagnosis using a rotor practical fault diagnosis case.

Design of a three-phase multistage axial flux permanent magnet generator for wind turbine applications

Presently, axial flux permanent magnet machines are becoming popular and are being deployed actively for low speed applications. This paper presents an improved model of a multistage axial flux permanent magnet generator (AFPMG). The multistage AFPMG consists of multiple stator and rotor discs. There are three identical 1-phase stator discs and four in-phase rotor discs in the proposed multistage AFPMG. In this research, 4 case studies were analyzed on the design of the multistage AFPMG. First, a phase shift model (PSM) positions the three 1-phase stator discs to behave as a 3-phase generator. Actually, the PSM computes phases for three stator discs in order to establish phase shift of 120$^{\circ}$ between each two phases. The implementation of the presented model in the multistage AFPMG reduces the diameter of the stator disc three times as compared to the conventional 3-phase AFPMG with identical rated specifications. Second, the voltage waveform of the AFPMG was analyzed for harmonic contents and the percentages of 3rd and 5th harmonics were computed. The test results show that 3rd and 5th harmonics were reduced to 10.7% and 0.54%, respectively, in voltage waveform. Third, the proposed multistage AFPMG was designed considering begin-to-end winding connections of the stator disc. While adopting begin-to-end connection, the number of poles of the AFPMG are doubled, which ultimately increases air-gap flux density and thus the terminal voltage of the stator disc and operating shaft speed is halved. The test results show that the torque-to-weight ratio parameter of the designed AFPMG was improved by using a begin-to-end connection for the stator disc. Fourth, the increased air-gap flux density also improves the power density parameter of the AFPMG with a begin-to-end winding connection. Moreover, a prototype model of a 1200-W multistage AFPMG was designed and fabricated while following PSM and begin-to-end winding connection and tested. Thus the test results verify the proposed model of the multistage AFPMG for wind turbine applications.