Electrothermal combined optimization on notch in air-cooled high-speed permanent-magnet generator

A 30kVA, 96000rpm, air cooled high-speed permanent magnetic generator (HSPMG) is investigated in this paper. Considering effects on both the magnetic circuit and heat transfer paths comprehensively, the stator slot notch in this HSPMG is optimized. First, by using the time-stepping finite element method, the transient electromagnetic fields of HSPMG is numerically calculated, and the electromagnetic losses in different components are obtained. Then, after the determination of other mechanical losses in such a machine, a three-dimensional fluid-thermal coupling calculation model is established, and the working temperature distribution in the HSPMG is studied. Thus, the electromagnetic-fluid-thermal coupling analysis method on the HSPMG is proposed, by using which the influences of machine notch height on machine magnetic circuit and cooling air flowing path are investigated. Meanwhile, both the electromagnetic performance and the temperature distribution in HSPMG with different stator notch height are studied, and a series of analytical equations are deduced to describe the variations of machine performances with stator notch. By using the proposed unbalance relative weighting method, the notch height is optimized to enhance the performance of HSPMG. The obtained conclusions could provide reference for HSPMG electromagnetic calculation, cooling system design, and optimization design

Health condition assessment of ball bearings using TOSELM

The health condition assessment of Electric Multiple Unit (EMU) traction motor ball bearing is one of the key issues of high-speed train running safety. In order to assess health condition of EMU traction motor ball bearing, an online-sequential extreme learning machine algorithm based on TensorFlow (TOSELM) is proposed. Samples data set is divided into normal condition and fault condition using vibration data of ball bearings. This paper uses health condition accuracy rate index to evaluate TOSELM algorithm performance. The proposed approach is verified by public data set and private data set. The experiment results show the proposed method is an effective method for ball bearing health status assessment

Sparse decomposition based on ADMM dictionary learning for fault feature extraction of rolling element bearing

Sparse decomposition is a novel method for the fault diagnosis of rolling element bearing, whether the construction of dictionary model is good or not will directly affect the results of sparse decomposition. In order to effectively extract the fault characteristics of rolling element bearing, a sparse decomposition method based on the over-complete dictionary learning of alternating direction method of multipliers (ADMM) is presented in this paper. In the process of dictionary learning, ADMM is used to update the atoms of the dictionary. Compared with the K-SVD dictionary learning and non-learning dictionary method, the learned ADMM dictionary has a better structure and faster speed in the sparse decomposition. The ADMM dictionary learning method combined with the orthogonal matching pursuit (OMP) is used to implement the sparse decomposition of the vibration signal. The envelope spectrum technique is used to analyze the results of the sparse decomposition for the fault feature extraction of the rolling element bearing. The experimental results show that the ADMM dictionary learning method can updates the dictionary atoms to better fit the original signal data than K-SVD dictionary learning, the high frequency noise in the vibration signal of the rolling bearing can be effectively suppressed, and the fault characteristic frequency can be highlighted, which is very favorable for the fault diagnosis of the rolling element bearing

On-line prediction remaining useful life for ball bearings via grey NARX

The Huge vibration data are generated continuously by many sensors in daily high-speed rotating machinery operations. Accurate online prediction based on big vibration data streaming can reduce the risks related to failures and avoid service disruptions. This paper presents a hybrid nonlinear autoregressive network with exogenous inputs (NARX) model to forecast the remaining useful life of ball bearings through health index based on big vibration data streaming. This approach is validated by a real data from PRONOSTIA experimentation platform and industrial test rig compared with backpropagation neural network (BP), Elman and general regression neural network (GRNN) prediction model. Root mean square error, mean absolute error and correlation coefficient were used as performance indexes to evaluate the prediction accuracy of these models. The mean absolute error, the root mean square error and the correlation coefficient of hybrid NARX model evaluation index are 2.04, 2.85 and 0.98 respectively. It shows that the model presented in this paper has higher prediction accuracy. It can meet the needs of actual ball bearing remaining useful life prediction and also provide reference in other fields

CQICO and multiobjective thermal optimization for high-speed PM generator

This paper proposes a novel Continuous Quantum Immune Clonal Optimization (CQICO) algorithm for thermal optimization on an 117kW high speed permanent magnet generator (HSPMG). The proposed algorithm mixes the Quantum Computation into the Immune Cloning Algorithm and causes better population diversity, higher global searching ability, and faster convergence which approved by simulation results. Then, the improved algorithm is applied to seek an optimized slot groove and improve HSPMG thermal performance, in which the 3-D fluid-thermal coupling analyses are processed with a multi-objective optimal group composed of the highest temperature and the temperature difference. Both the proposed algorithm and the obtained conclusions are of significances in the design and optimization of the cooling system in electric machines

Electromagnetic Analysis and Optimization of High-speed Maglev Linear Synchronous Motor Based on Field-circuit Coupling

High speed maglev train has become a new non-contact transportation mode mainly studied in recent years because of its non-sticking and high speed characteristics. Firstly, the finite element model of the long stator linear synchronous motor(LSM) is established based on the structure of the test prototype. After calculation, it is compared with the experimental data and verified. On this basis, a field-circuit coupling model based on inverter circuit is established, and the influence of carrier wave ratio change on the output characteristics of LSM is calculated and analyzed. Finally, the filter circuit is introduced into the field-circuit coupling model, and the influence of the filter circuit on the output characteristics of the LSM is compared and analyzed

Harmonic Loss Analysis of the Traction Transformer of High-Speed Trains Considering Pantograph-OCS Electrical Contact Properties

The traction transformer of the traction drive system of a high-speed train is one of the main equipments for energy conversion. The transformer loss will be increased by load harmonics and pantograph arcs at high speed. It is very important to predict losses for the improvement of traction transformer design. In this paper, a dynamic model of the pantograph-catenary system is established using the MSC.Marc software based on the finite element method to analyze disconnection events in different speeds. Then the pantograph arc, traction transformer and four-quadrant converter model is set up. Resistance variations with the change of harmonic frequency have been considered in the calculation formulae of harmonic losses. Traction transformer losses can be calculated based on the harmonic T-equivalent circuit and superposition principle. Considering the harmonic losses variations, the effects of arc voltage on harmonic copper loss and harmonic core loss are analyzed, respectively. The average loss at different disconnection ratios is also calculated. This method could be used to estimate the increment of transformer harmonic losses with poor current conditions at high speed

Comparative Analysis of Bearing Current in Wind Turbine Generators

Bearing current problems frequently appear in wind turbine systems, which cause wind turbines the break down and result in very large losses. This paper investigates and compares bearing current problems in three kinds of wind turbine generators, namely doubly-fed induction generator (DFIG), direct-drive permanent magnet synchronous generator (PMSG), and semi-direct-drive PMSG turbines. Common mode voltage (CMV) of converters is introduced firstly. Then stray capacitances of three kinds of generators are calculated and compared through the finite element method. The bearing current equivalent circuits are proposed and simulations of the bearing current are carried out. It is verified that the bearing currents of DFIGs are more serious than the two kinds of PMSG, while common mode current (CMC) of the direct-drive PMSG is much greater than the other two types of wind turbine generators

Influence of the Variable Cross-Section Stator Ventilation Structure on the Temperature of an Induction Motor

The performance of an induction motor, a core component of the high-speed train, is of critical importance to the safety of the train. As a result of limited space in the train and the motor’s high-power density, motor heating poses a grave threat to its service life and operational safety. In this study, a 600-kW high-speed train induction motor model was established and its temperature field calculated by the finite volume method. To optimize the heat dissipation and further reduce the motor temperature rise, a variable cross-section stator ventilation hole was proposed and its influence on the wind velocity and temperature rise comprehensively studied. After comparing the cooling effect of the linear and nonlinear variable cross-section of the ventilation hole, the influence of the cross-sectional diameter and the radial position of the ventilation hole on the temperature rise was explored. Finally, the most favorable scheme for motor heat dissipation was determined