• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.3
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• pp.330-335
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• 2012

Brushless doubly-fed machine (BDFM) doesn't use brush and slip ring, and has advantages such as high system reliability, small capacity of its frequency converter, low system cost, adjustable power factor and speed, etc. At the same time, it has good applicable potentials on the variable frequency motors and the variable speed constant frequency generators. However, due to the complicacy and particularity of BDFM in the structure and operating mechanism, the effect of magnetic field modulation directly influences the operating efficiency of BDFM. To study the effect of different cage rotor structures on the magnetic field modulation of BDFM, the rotor magnetomotive force (MMF) of BDFM with cage rotor is studied by the analytical method. The components and features of rotor harmonic MMFs are discussed. At the same time, the method to weaken the higher harmonics is analyzed by the theoretic formulae. Furthermore, the magnetic field modulation mechanism is expounded on in detail and the relationship between the magnetic field modulation effect and the operating efficiency of BDFM is established. And then, a new method for estimating the magnetic field modulation effect is proposed. At last, the magnetic field modulation effects of four BDFM prototypes with different cage rotor structures are compared by the MMF analysis and the efficiency data of electromagnetic design. The results verify the effectiveness of the new method for estimating the magnetic field modulation effect of BDFM with cage rotor.

• Journal of Power Electronics
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• v.16 no.1
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• pp.259-267
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• 2016

This paper presents a stand-alone variable speed constant frequency (VSCF) ship shaft generator system based on a brushless doubly-fed machine (BDFM). In this system, the output voltage amplitude and frequency of the BDFM are kept constant under a variable rotor speed and load by utilizing a well-designed current vector controller to regulate the control winding (CW) current. The control scheme is proposed, and the hardware design for the control system is developed. The proposed generator system is tested on a 325 TEU container vessel, and the test results show the good dynamic performance of the CW current vector controller and the whole control system. A harmonic analysis of the output voltage and a fuel consumption analysis of the generator system are also implemented. Finally, the total efficiency of the generator system is presented under different rotor speeds and load conditions.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.69-76
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• 2011

Matching customers becomes the key function in on-line mediate services. There are two matching methods: one-directional matching that requires requests from one side(e,g., information searching), bi-directional matching that considers requests from both sides. Previous bi-directional matching has difficulties of getting the interests explicitly and service collapse problems when the opposite side do not put responding interests. This paper attempts to automate the inputs of interests for bi-directional matching by calculating the interests with fuzzy matching algorithm for optimization. The results of the proposed Bi-directional Fuzzy Matching(BDFM) algorithm told that the job placement accuracy of employment information matching results is over 95%. And, BDFM gives statically significant positive effect for motivating the employment activities when analyzed the effect after completing the implementation.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.23-29
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• 2021

Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.