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Abstract

In this paper, a low kilo-volt-ampere rating zigzag connected autotransformer based 36-pulse rectifier system supplying vector controlled induction motor drives (VCIMD) is designed, modeled and simulated. Detailed design procedure and magnetic rating calculation of the proposed autotransformer and interphase reactor is studied. Moreover, the design process of the autotransformer is modified to make it suitable for retrofit applications. Simulation results confirm that the proposed 36-pulse rectifier system is able to suppress less than 35th harmonics in the utility line current. The influence of load variation and load character is also studied to demonstrate the performance and effectiveness of the proposed 36-pulse rectifiers. A set of power quality indices at AC mains and DC link are presented to compare the performance of 6-, 24- and 36-pulse AC-DC converters.
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Authors and Affiliations

Xiao-Qiang Chen
Chun-Ling Hao
Qiu Hao
Li Min
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Abstract

To reduce the influence of the static unbalance on an infrared missile guidance system, a new static unbalance measure system for the gimbals axes has been developed. Considering the coupling effects caused by a mass eccentricity, the static balance condition and measure sequence for each gimbal axis are obtained. A novel static unbalance test approach is proposed after analyzing the dynamic model of the measured gimbal axis. This approach is to drive the measured gimbal axis to do sinusoidal reciprocating motion in a small angle and collect its drive currents in real time. Then the static unbalance of the measured gimbal axis can be obtained by the current multi-cycle integration. Also a measuring system using the proposed approach has been developed. A balanced simulator is used to verify the proposed approach by the load and repeatability tests. The results show the proposed approach enhances the efficiency of the static unbalance measurement, and the developed measuring system is able to achieve a high precision with a greater stability.
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Authors and Affiliations

Hui Yang
Yan Zhao
Min Li
Falin Wu
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Abstract

The microphone data collected in aeroacoustic wind tunnel test contains not only desired aeroacoustic signal but also background noise generated by the jet or the valve of the wind tunnel, so the desired aeroacoustic characteristics is difficult to be highlighted due to the low Signal-to-Noise Ratio (SNR). Classical cross spectral matrix removal can only reduce the microphone self-noise, but its effect is limited for jet noise. Therefore, an Airflow Background Noise Suppression method based on the Ensemble Empirical Mode Decomposition (ABNSEEMD) is proposed to eliminate the influence of background noise on aeroacoustic field reconstruction. The new method uses EEMD to adaptively separate the background noise in microphone data, which has good practicability for increasing SNR of aeroacoustic signal. A localization experiment was conducted by using two loudspeakers in wind tunnel with 80 m/s velocity. Results show that proposed method can filter out the background noise more effectively and improve the SNR of the loudspeakers signal compared with spectral subtraction and cepstrum methods. Moreover, the aeroacoustic field produced by a NACA EPPLER 862 STRUT airfoil model was also measured and reconstructed. Delay-and-sum beamforming maps of aeroacoustic source were displayed after the background noise was suppressed, which further demonstrates the proposed method’s advantage.
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Authors and Affiliations

Yuanwen Li
1
Min Li
2 3
Daofang Feng
2
Debin Yang
1
Long Wei
4

  1. School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  2. Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
  3. Key Laboratory of Fluid Interaction with Material, Ministry of Education, University of Science and Technology Beijing, Beijing 100083, China
  4. Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering, Beijing 100076, China

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