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RISS 인기검색어
- 검색키워드
- 저자 : Alireza Sadoughi (검색결과 7 건)
- 무료
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Intelligent Diagnosis of Broken Bars in Induction Motors Based on New Features in Vibration Spectrum
Sadoughi, Alireza,Ebrahimi, Mohammad,Moallem, Mehdi,Sadri, Saeid The Korean Institute of Power Electronics 2008 JOURNAL OF POWER ELECTRONICS Vol.8 No.3
Many induction motor broken bar diagnosis methods are based on evaluating special components in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to a broken rotor fault are slip dependent, therefore, correct diagnosis of fault - especially when obtrusive frequency components are present - depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosis method based on only a vibration sensor. Motor velocity oscillation due to a broken rotor causes frequency components at twice slip frequency difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in a vibration spectrum, therefore th motor slip can be computed. Now components related to rotor fault can be found. It is shown that a trained neural network - as a substitute for an expert person - can easily categorize the existence and the severity of a fault according to the features extracted from the presented method. This method requires no information about th motor internal and has been able to diagnose correctly in all the laboratory tests.
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Intelligent Diagnosis of Broken Bars in Induction Motors Based on New Features in Vibration Spectrum
Alireza Sadoughi,Mohammad Ebrahimi,Mehdi Moallem,Saeid Sadri 전력전자학회 2008 JOURNAL OF POWER ELECTRONICS Vol.8 No.3
Many induction motor broken bar diagnosis methods are based on evaluating special components in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to a broken rotor fault are slip dependent, therefore, correct diagnosis of fault - especially when obtrusive frequency components are present - depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosis method based on only a vibration sensor. Motor velocity oscillation due to a broken rotor causes frequency components at twice slip frequency difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in a vibration spectrum, therefore the motor slip can be computed. Now components related to rotor fault can be found. It is shown that a trained neural network - as a substitute for an expert person - can easily categorize the existence and the severity of a fault according to the features extracted from the presented method. This method requires no information about the motor internal structure and has been able to diagnose correctly in all the laboratory tests.
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Cogging Torque Reduction in Line Start Permanent Magnet Synchronous Motor
Hamidreza Behbahanifard,Alireza Sadoughi 대한전기학회 2016 Journal of Electrical Engineering & Technology Vol.11 No.4
Cogging torque has a negative impact on the operation of permanent magnet machines by increasing torque ripple, speed ripple, acoustic noise and vibration. In this paper Magnet Shifting Method has been used as a tool to reduce the cogging torque in inset Line Start Permanent Magnet Synchronous Motor (LSPMSM). It has been shown that Magnet Shifting Method can effectively eliminate several lower-order harmonics of cogging torque. In order to implement the method, first the expression of cogging torque is studied based on the Fourier analysis. An analytical expression is then introduced based on Permanent Magnet Shifting to reduce cogging torque of LSPMS motors. The method is applied to some existing machine designs and their performances are obtained using Finite Element Analysis (FEA). The effect of magnet shifting on pole mmf (magneto motive force) distribution in air gap is discussed. The side effects of magnet shifting on back-EMF, core losses and torque profile distortion are taken into account in this investigation. Finally the experimental results on two prototypes 24 slot 4 pole inset LSPMS motors have been used to validate the theoretical analysis.
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Cogging Torque Reduction in Line Start Permanent Magnet Synchronous Motor
Behbahanifard, Hamidreza,Sadoughi, Alireza The Korean Institute of Electrical Engineers 2016 Journal of Electrical Engineering & Technology Vol.11 No.4
Cogging torque has a negative impact on the operation of permanent magnet machines by increasing torque ripple, speed ripple, acoustic noise and vibration. In this paper Magnet Shifting Method has been used as a tool to reduce the cogging torque in inset Line Start Permanent Magnet Synchronous Motor (LSPMSM). It has been shown that Magnet Shifting Method can effectively eliminate several lower-order harmonics of cogging torque. In order to implement the method, first the expression of cogging torque is studied based on the Fourier analysis. An analytical expression is then introduced based on Permanent Magnet Shifting to reduce cogging torque of LSPMS motors. The method is applied to some existing machine designs and their performances are obtained using Finite Element Analysis (FEA). The effect of magnet shifting on pole mmf (magneto motive force) distribution in air gap is discussed. The side effects of magnet shifting on back-EMF, core losses and torque profile distortion are taken into account in this investigation. Finally the experimental results on two prototypes 24 slot 4 pole inset LSPMS motors have been used to validate the theoretical analysis.
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Multi-objective Bayesian optimization of super hydrophobic coatings on asphalt concrete surfaces
Ali Nahvi,Mohammad Kazem Sadoughi,Ali Arabzadeh,Alireza Sassani,Chao Hu,Halil Ceylan,Sunghwan Kim 한국CDE학회 2019 Journal of computational design and engineering Vol.6 No.4
Conventional snow removal strategies add direct and indirect expenses to the economy through profit lost due to passenger delays costs, pavement durability issues, contaminating the water runoff, and so on. The use of superhydrophobic (super-water-repellent) coating methods is an alternative to conven-tional snow and ice removal practices for alleviating snow removal operations issues. As an integrated experimental and analytical study, this work focused on optimizing superhydrophobicity and skid resis-tance of hydrophobic coatings on asphalt concrete surfaces. A layer-by-layer (LBL) method was utilized for spray depositing polytetrafluoroethylene (PTFE) on an asphalt concrete at different spray times and variable dosages of PTFE. Water contact angle and coefficient of friction at the microtexture level were measured to evaluate superhydrophobicity and skid resistance of the coated asphalt concrete. The opti-mum dosage and spay time that maximized hydrophobicity and skid resistance of flexible pavement while minimizing cost were estimated using a multi-objective Bayesian optimization (BO) method that replaced the more costly experimental procedure of pavement testing with a cheap-to-evaluate surrogate model constructed based on kriging. In this method, the surrogate model is iteratively updated with new experimental data measured at proper input settings. The result of proposed optimization method showed that the super water repellency and coefficient of friction were not uniformly increased for all the specimens by increasing spray time and dosage. In addition, use of the proposed multi-objective BO method resulted in hydrophobicity and skid resistance being maximally augmented by approximately 23% PTFE dosage at a spray time of 5.5 s.
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