Anti-Phase Vortex Reduction Control for Rotor Noise Suppression

2021 ◽  
Author(s):  
Nhan T. Nguyen ◽  
Juntao Xiong ◽  
Raja Zahirudin ◽  
Sihong Yan ◽  
Jose Palacios
Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. G69-G76 ◽  
Author(s):  
Jianghai Xia ◽  
William E. Doll ◽  
Richard D. Miller ◽  
T. Jeffrey Gamey ◽  
Abraham M. Emond

A unique filtering approach is developed to eliminate helicopter rotor noise. It is designed to suppress harmonic noise from a rotor that varies slightly in amplitude, phase, and frequency and that contaminates aeromagnetic data. The filter provides a powerful harmonic noise-suppression tool for data acquired with modern large-dynamic-range recording systems. This three-step approach — polynomial fitting, bandpass filtering, and rotor-noise synthesis — significantly reduces rotor noise without altering the spectra of signals of interest. Two steps before hum filtering — polynomial fitting and bandpass filtering — are critical to accurately model the weak rotor noise. During rotor-noise synthesis, amplitude, phase, and frequency are determined. Data are processed segment by segment so that there is no limit on the length of data. The segment length changes dynamically along a line based on modeling results. Modeling the rotor noise is stable and efficient. Real-world data examples demonstrate that this method can suppress rotor noise by more than 95% when implemented in an aeromagnetic data-processing flow.


1990 ◽  
Vol 88 (4) ◽  
pp. 2050-2050
Author(s):  
Kenzo Ishimaru

2000 ◽  
Author(s):  
Edward Awh ◽  
John Serences ◽  
Kelsey Libner ◽  
Michi Matsukura

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.


2018 ◽  
Vol 138 (5) ◽  
pp. 593-602 ◽  
Author(s):  
Arata Kawamura ◽  
Takahiro Yamashita ◽  
Youji Iiguni

2020 ◽  
Vol E103.B (9) ◽  
pp. 899-902
Author(s):  
Sho MUROGA ◽  
Motoshi TANAKA ◽  
Takefumi YOSHIKAWA ◽  
Yasushi ENDO

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