suppression method
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2021 ◽  
Vol 12 (1) ◽  
pp. 198
Author(s):  
Liangjie Jia ◽  
Peng Rao ◽  
Xin Chen ◽  
Shanchang Qiu

The blind pixel suppression is the key preprocess to guarantee the real-time space-based infrared point target (IRPT) detection and tracking. Meanwhile, flickering pixels, as one of the blind pixels, is hard to suppress because of randomness. At present, common methods adopting a single feature generally need to accumulate dozens or hundreds of frames to ensure detection accuracy, which cannot update flickering pixels frequently. However, with low detection frequency, the flickering pixels are easily miss detected. In this paper, we propose an on-board flickering pixel dynamic suppression method based on multi-feature fusion. The visual and motion features of flickering pixels are extracted from the result of IRPT detection and tracking. Then, the confidence of flickering pixel evaluation strategy and selection mechanism of flickering pixel are introduced to fuse the above features, which achieves accurate flickering pixel suppression using a dozen frames. The experimental results evaluated on the real image of four scenarios show that the blind pixel false detection rate of the proposed method is no more than 1.02%. Meanwhile, evaluated on the simulated image, the flickering pixel miss suppression rate is no more than 2.38%, and the flickering pixel false suppression rate is 0. The proposed method could be an addition to most other IRPT detection methods, which guarantees the near-real-time and reliability of on-board IRPT detection applications.


Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8579
Author(s):  
Linao Li ◽  
Xinlao Wei

Partial discharge detection is an important means of insulation diagnosis of electrical equipment. To effectively suppress the periodic narrowband and white noise interferences in the process of partial discharge detection, a partial discharge interference suppression method based on singular value decomposition (SVD) and improved empirical mode decomposition (IEMD) is proposed in this paper. First, the partial discharge signal with periodic narrowband interference and white noise interference x(t) is decomposed by SVD. According to the distribution characteristics of single values of periodic narrowband interference signals, the singular value corresponding to periodic narrowband interference is set to zero, and the signal is reconstructed to eliminate the periodic narrowband interference in x(t). IEMD is then performed on x(t). Intrinsic mode function (IMF) is obtained by EMD, and based on the improved 3σ criterion, the obtained IMF components are statistically processed and reconstructed to suppress the influence of white noise interference. The methods proposed in this paper, SVD and SVD + EMD, are applied to process the partial discharge simulation signal and partial discharge measurement signal, respectively. We calculated the signal-to-noise ratio, normalized correlation coefficient, and mean square error of the three methods, respectively, and the results show that the proposed method suppresses the periodic narrowband and white noise interference signals in partial discharge more effectively than the other two methods.


2021 ◽  
Vol 2136 (1) ◽  
pp. 012012
Author(s):  
Shengqing Li ◽  
Xin Yao ◽  
Ziran Peng ◽  
Zhichao Shen

Abstract Photo-voltaic inverts usually use LCL filter for filtering, and LCL filter will bring resonance problems to the system. This paper focuses on invert-er side current feedback control (invert-er side current feedback, ICF). This paper proposes a method for suppressing resonance of photo-voltaic invert-er clusters based on capacitor voltage feed-forward. First, establish the ICF mathematical model based on HPF and CVF under the weak grid, qualitatively analyze the resonance mechanism of the cluster invert-er, then analyze the system control structure and stability according to the proposed method, and finally verify the effectiveness of the proposed method through simulation and experiment sexuality and correctness.


2021 ◽  
Author(s):  
Rino Okochi ◽  
Hiroyuki Takatsuji ◽  
Jun Imaoka ◽  
Masayoshi Yamamoto
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