The Electromagnetic-Fluid-Temperature Field Analysis of Loss and Heat of Self-Cooling Separate-Phase Enclosed Bus of Large Generator

Fan, Zhaolin; Bian, Zu-Ying; Xiao, Ke; Li, Jing-Can; Yao, Bing; Gan, Xue-Gui

doi:10.1109/access.2021.3051241

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…The model of the motor is solved using the field-circuit coupled time-domain finite element method [46,47]. As the motor takes time to transition from start-up to stable running condition.…”

Section: Finite Element Solution Parameter Settingmentioning

confidence: 99%

Adaptive Parameter Selection Variational Mode Decomposition Based on Bayesian Optimization and Its Application to the Detection of ITSC in PMSM

Xia,

Wang,

2024

IEEE Access

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Permanent magnet synchronous motor (PMSM) is a vital component of modern industry which is widely used in transport, aerospace and intelligent machinery. In the light of its relatively high frequency of inter-turn short circuit (ITSC) fault, it is valuable to detect the fault accurately and efficiently. Due to the convenience of motor vibration signal measurement, more attention has been paid to fault detection methods based on vibration signal. As a nonstationary, nonlinear signal, vibration signal is highly susceptible to external noise interference. Variational mode decomposition (VMD) has a wide range of applications in the field of nonlinear signal analysis, but the processing ability to the signal is affected by the parameter setting. Hence, a Bayesian optimized adaptive parameter selection variational mode decomposition (BOAPS-VMD) signal processing method is proposed and applied to detect the ITSC in PMSM. Firstly, the motor vibration signal is decomposed through BOAPS-VMD, and the intrinsic mode functions (IMFs) are obtained. Secondly, the cumulative variance contribution rate (C-VCR) is applied to identify the IMFs that contain fault signature information. Finally, using Hilbert transform (HT) to further analyze the IMFs that are identified. The results are output in 3D time-frequency diagrams to enhance the representation of fault signatures. The effectiveness and accuracy of the BOAPS-VMD were validated through the finite element simulation and experiment. The study shows that the BOAPS-VMD effectively improves the modal mixing phenomenon, has better noise robustness, improves the accuracy of fault detection, and has better engineering applicability.INDEX TERMS Permanent magnet synchronous motor (PMSM), fault detection, variational mode decomposition (VMD), Bayesian optimization, Hilbert transform (HT)

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Section: Finite Element Solution Parameter Settingmentioning

confidence: 99%

Adaptive Parameter Selection Variational Mode Decomposition Based on Bayesian Optimization and Its Application to the Detection of ITSC in PMSM

Xia,

Wang,

2024

IEEE Access

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“…In recent years, many studies have been conducted on the fluid field and temperature field of the generator [3,4] using the finite element method [5][6][7] and the finite volume method (FVM) [8][9][10][11][12]. In order to simplify the model and improve the calculation efficiency, the two-dimensional finite element model is often adopted [13].…”

Section: Introductionmentioning

confidence: 99%

Effect of gas compressibility on fluid field of air‐cooled turbo‐generator

Liu

Ding

et al. 2022

IET Electric Power Appl

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The effect of gas compressibility on the fluid flow characteristics of a 350 MW air-cooled turbo-generator is investigated in this paper. Two gas models taking gas compressibility and incompressibility into account are established for numerical calculation. Then, a onefourth physical model based on the practical ventilation structure and basic assumption is built to analyse the flow velocity and flow rate using the finite volume method (FVM). The FVM-predicted flow rate and flow velocity of cooling medium in the air cavity, stator and rotor of the generator show the distribution characteristics of flow rate and velocity in the generator is affected by the gas compressibility model selection. The comparison of FVM-predicted flow rate and experimental value shows that the FVMpredicted results using the gas compressibility model is more accurate when comparing to those using the incompressible model. Therefore, the gas compressibility model is an appealing approach to analyse the flow fluid characteristics of the air-cooled turbo-generator.

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“…3-D FEM and analytical method are two main methods for calculating the above problems. Based on 3-D transient FEM, the magnetic field and eddy current losses in the end region of large electrical machine were calculated in [3][4], and the temperature distribution in the end region of the water-hydrogen cooled turbine generator was calculated in [5][6][7][8] Author (e-mail: xxxx@126.com).…”

Section: Introductionmentioning

confidence: 99%

Improved Analytical Algorithm for Magnetic Field of End Windings in 300Mvar Synchronous Condenser

et al. 2021

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The magnetic field of end windings affects the leakage reactance of end windings and the eddy current losses of end structures in the large electrical machine. With the rising of single-machine capacity, such effect becomes more obvious. However, due to the complexity of end structures of large electrical machine, it will cause difficulty in meshing and long calculation time to calculate the magnetic field of end windings by using 3-D finite element method (FEM). In order to calculate the magnetic field of end windings quickly and accurately, an improved analytical algorithm (IAA) is proposed based on the mirror image principle, which takes into account the influence of stator back core and air-gap on the magnetic field of end windings by adding the fictitious boundary current and air-gap current, respectively. Taking a 300Mvar synchronous condenser (SC) as an example, the boundary current, air-gap current and magnetic field of end windings are calculated. Then, the influence of stator back core and stator involute segment current on the magnetic field of end windings are analyzed, which provides a theoretical support for the design and optimization of SC. To validate the accuracy of IAA, the calculation result is compared with 3-D FEM.INDEX TERMS Synchronous condenser, magnetic field, analytical algorithm, mirror image, stator back core.

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The Electromagnetic-Fluid-Temperature Field Analysis of Loss and Heat of Self-Cooling Separate-Phase Enclosed Bus of Large Generator

Cited by 6 publications

References 4 publications

Adaptive Parameter Selection Variational Mode Decomposition Based on Bayesian Optimization and Its Application to the Detection of ITSC in PMSM

Adaptive Parameter Selection Variational Mode Decomposition Based on Bayesian Optimization and Its Application to the Detection of ITSC in PMSM

Effect of gas compressibility on fluid field of air‐cooled turbo‐generator

Improved Analytical Algorithm for Magnetic Field of End Windings in 300Mvar Synchronous Condenser

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