Flow aeration by an offset aerator: air entrainment, bubbly flow turbulence, and adaptive-window cross-correlation processing

Author(s):  
Xuechun LIU ◽  
Ruidi BAI ◽  
Hang WANG ◽  
Shanjun LIU
Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5878
Author(s):  
María Campo-Valera ◽  
Ivan Felis-Enguix ◽  
Isidro Villó-Pérez

For years, in the field of underwater acoustics, a line of research with special relevance for applications of environmental monitoring and maritime security has been developed that explores the possibilities of non-linear phenomena of sound propagation, especially referring to the so-called parametric effect or self-modulation. This article shows the results of using a new modulation technique based on sine-sweep signals, compared to classical modulations (FSK and PSK). For each of these modulations, a series of 16-bit strings of information with different frequencies and durations have been performed, with the same 200 kHz carrier wave. All of them have been tested in the Hydroacoustic Laboratory of the CTN and, through the application of cross-correlation processing, the limitations and improvements of this novel processing technique have been evaluated. This allows reaching better limits in discrimination of bits and signal-to-noise ratio used in underwater parametric acoustic communications.


2019 ◽  
Vol 9 (11) ◽  
pp. 2357 ◽  
Author(s):  
Niccolò Dematteis ◽  
Daniele Giordan ◽  
Paolo Allasia

In Earth Science, image cross-correlation (ICC) can be used to identify the evolution of active processes. However, this technology can be ineffective, because it is sometimes difficult to visualize certain phenomena, and surface roughness can cause shadows. In such instances, manual image selection is required to select images that are suitably illuminated, and in which visibility is adequate. This impedes the development of an autonomous system applied to ICC in monitoring applications. In this paper, the uncertainty introduced by the presence of shadows is quantitatively analysed, and a method suitable for ICC applications is proposed: The method automatically selects images, and is based on a supervised classification of images using the support vector machine. According to visual and illumination conditions, the images are divided into three classes: (i) No visibility, (ii) direct illumination and (iii) diffuse illumination. Images belonging to the diffuse illumination class are used in cross-correlation processing. Finally, an operative procedure is presented for applying the automated ICC processing chain in geoscience monitoring applications.


2020 ◽  
Author(s):  
Diako Hariri Naghadeh ◽  
Chris Bean

<p>To create virtual shot gather from passive signals it is essential to cross-correlate all the signals with the reference trace. Since surface sources dominate the origin of seismic noise, the correlated sections are highly dominated by surface waves. If the target is surface wave inversion general cross-correlation will suit the target. But if the extraction of body waves from those signals is the main objective, coherent ground roll events mask the body waves making it difficult to extract them. To tackle this issue a frequency-spatial nonCoherent filter (FX-NCF) plus a post-correlation processing module are introduced. FX-NCF is a prediction filter and the filter operator is a function of frequency, station interval and the slope of the interested event. In the frequency domain, the filter is looking for the prediction of n-th trace coherence spectrum from the (n-1)-th signal’s coherence spectrum by minimizing the objective function. Hybrid norms used to minimize the error. The coherence spectrum of each trace is the coherency between the reference signal and the desired trace. Applying the FX-NCF on 2D real recorded passive signals shows its superiority over general cross-correlation, deconvolution interferometry, cross-coherence and multi-taper-method-coherence-estimation methods in highlighting surface and body waves also improving the signal-to-noise (S/N) ratio. To show the necessity of post correlation processing (before applying on real recorded signals) to highlight reflection events, hyperbolic Radon transform (HRT) as a suitable post-correlation module applied on correlated section due to applied FX-NCF on simulated passive signals from a simple 2D synthetic model. The result encouraged us to apply the same hybrid modules (FX-NCF plus HRT) on real recorded passive signals to reconstruct wanted reflection events.</p>


2012 ◽  
Vol 588-589 ◽  
pp. 948-952
Author(s):  
Wei Zhang ◽  
Jin Fang Cheng ◽  
Jie Xu

At present the cross-correlation processing can only suppress the isotropic noise by vector hydrophone sound pressure and vibration velocity combined. The coherent composition of the actual ambient noise makes the detection ability of cross-correlation spectrum reduced. Use XWVD theory, proposed a cross symmetry-correlation function (Cross-SCF). Analysis of simulation data under different SNR and Different nature noise combination proving that the noise suppression Performance of suggested Cross-SCF has nothing to do with noise properties, and compared with the cross-correlation processing have indeed better than coherent noise suppression ability.


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