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    黄向华

    • 教授 博士生导师
    • 招生学科专业:
      动力工程及工程热物理 -- 【招收博士、硕士研究生】 -- 能源与动力学院
      航空宇航科学与技术 -- 【招收博士、硕士研究生】 -- 能源与动力学院
      能源动力 -- 【招收博士、硕士研究生】 -- 能源与动力学院
    • 毕业院校:南京航空航天大学
    • 学历:南京航空航天大学
    • 学位:工学博士学位
    • 所在单位:能源与动力学院
    • 联系方式:xhhuang@nuaa.edu.cn
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    Propeller synchrophasing control with a cylindrical scaled fuselage based on an improved data selection algorithm

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    所属单位:能源与动力学院

    发表刊物:Energies

    摘要:Propeller synchrophasing control is an active noise control method which can effectively reduce the noise in the cabin of a turboprop aircraft. The propeller signature model identified by the measured acoustic noise data is easily affected by flight speed, altitude, and the existence of the fuselage. Meanwhile, the noise excited by the propellers is nonstationary signal, which often fluctuates greatly, thus affecting the accuracy of the identification of the model. In this paper, a synchrophasing control experimental platform with a cylindrical scaled fuselage on ground is firstly established to validate the actual noise reduction in the cabin. Then, a minimum fluctuation data selection method based on wavelet filtering and three-parameter sinusoidal fitting is proposed to improve the identification accuracy of the propeller signature model. This method extracts the high-precision propeller blade passing frequency signal from the noise signal by using a wavelet filtering algorithm and selects the minimum fluctuation data segment by using a three-parameter sinusoidal fitting algorithm. The experimental results firstly show the significant noise attenuation achieved in the cabin using propeller synchrophasing control. Secondly, the propeller signature model improved by the minimum fluctuation data selection method has higher accuracy than that identified by the traditional method. © 2019 by the authors.

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    发表时间:2019-01-01

    合写作者:Sheng, Long,Cao, Yunfei

    通讯作者:黄向华