Source localization with three-dimensional sound intensity probe with high precision

2017 ◽  
Vol 141 (5) ◽  
pp. 3587-3587 ◽  
Author(s):  
Jeong-Guon Ih ◽  
In-Jee Jung ◽  
Jung-Han Woo
Keyword(s):  
High Precision ◽  
Source Localization ◽  
Three Dimensional ◽  
Sound Intensity

Three-dimensional auto-stereoscopic animated image with a long viewing distance using high-precision image correction

2009 ◽  
Author(s):  
Takehito Teraguchi ◽  
Hiromasa Yamashita ◽  
Ken Masamune ◽  
Takeyoshi Dohi ◽  
Hongen Liao
Keyword(s):  
High Precision ◽  
Three Dimensional ◽  
Viewing Distance ◽  
Image Correction

scholarly journals Heating source localization in a reduced time

2016 ◽  
Vol 26 (3) ◽  
pp. 623-640 ◽  
Author(s):  
Sara Beddiaf ◽  
Laurent Autrique ◽  
Laetitia Perez ◽  
Jean-Claude Jolly
Keyword(s):  
Heat Conduction ◽  
Source Localization ◽  
Conjugate Gradient ◽  
Regularization Method ◽  
Three Dimensional ◽  
Gradient Algorithm ◽  
Iterative Regularization ◽  
Heating Source ◽  
Ill Posed ◽  
Reduced Time

Abstract Inverse three-dimensional heat conduction problems devoted to heating source localization are ill posed. Identification can be performed using an iterative regularization method based on the conjugate gradient algorithm. Such a method is usually implemented off-line, taking into account observations (temperature measurements, for example). However, in a practical context, if the source has to be located as fast as possible (e.g., for diagnosis), the observation horizon has to be reduced. To this end, several configurations are detailed and effects of noisy observations are investigated.

scholarly journals Parallel, linear, and subnanometric 3D tracking of microparticles with Stereo Darkfield Interferometry

2021 ◽  
Vol 7 (6) ◽  
pp. eabe3902
Author(s):  
Martin Rieu ◽  
Thibault Vieille ◽  
Gaël Radou ◽  
Raphaël Jeanneret ◽  
Nadia Ruiz-Gutierrez ◽  
...  
Keyword(s):  
High Precision ◽  
High Throughput ◽  
Single Molecule ◽  
Particle Tracking ◽  
Focal Plane ◽  
Tracking System ◽  
Three Dimensional ◽  
3D Tracking ◽  
Single Molecule Force Spectroscopy ◽  
A New Technique

While crucial for force spectroscopists and microbiologists, three-dimensional (3D) particle tracking suffers from either poor precision, complex calibration, or the need of expensive hardware, preventing its massive adoption. We introduce a new technique, based on a simple piece of cardboard inserted in the objective focal plane, that enables simple 3D tracking of dilute microparticles while offering subnanometer frame-to-frame precision in all directions. Its linearity alleviates calibration procedures, while the interferometric pattern enhances precision. We illustrate its utility in single-molecule force spectroscopy and single-algae motility analysis. As with any technique based on back focal plane engineering, it may be directly embedded in a commercial objective, providing a means to convert any preexisting optical setup in a 3D tracking system. Thanks to its precision, its simplicity, and its versatility, we envision that the technique has the potential to enhance the spreading of high-precision and high-throughput 3D tracking.

Absolute Measurement of Aspheric Surfaces Using White-Light Interferometry

2007 ◽  
Vol 364-366 ◽  
pp. 80-85
Author(s):  
Su Ping Chang ◽  
Tie Bang Xie ◽  
Xuang Ze Wang ◽  
Jun Guo
Keyword(s):  
High Precision ◽  
White Light ◽  
Spherical Surface ◽  
Three Dimensional ◽  
Influence Factors ◽  
Horizontal Displacement ◽  
Absolute Measurement ◽  
Aspheric Surfaces ◽  
Interferometric Technique ◽  
Main Influence

White-light interferometric technique has been widely applied in the measurement of three-dimensional profiles and roughness with high-precision. Based on the characteristic of interferometric technique, a new method combined with image location and a three-dimensional stage is proposed to achieve the non-contact absolute shape measurement for aspheric and spherical surface in a slarge range. The interference fringes vary with the horizontal displacement of the measured surface, the surface information was obtained by locating the transformation of the maximal intensity in the interferograms. Two main influence factors are discussed; they are performance of the inerferimetric microscope and the stage. Since the performance of the stage directly determines the measurement precision, a three-dimensional displacement stage with a large range and a high precision was developed. Some experiments were carried out to verify the performance of the three-dimensional displacement stage and the validity of the new measurement method with satisfactory results.

Inverse methods in aeroacoustic three-dimensional volumetric noise source localization and quantification

2020 ◽  
Vol 473 ◽  
pp. 115208 ◽  
Author(s):  
G. Battista ◽  
P. Chiariotti ◽  
M. Martarelli ◽  
P. Castellini
Keyword(s):  
Source Localization ◽  
Noise Source ◽  
Three Dimensional ◽  
Inverse Methods

scholarly journals Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines

2020 ◽  
Vol 17 (162) ◽  
pp. 20190616 ◽  
Author(s):  
Ben J. Wolf ◽  
Jos van de Wolfshaar ◽  
Sietse M. van Netten
Keyword(s):  
Neural Network ◽  
Source Localization ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Sensory System ◽  
Three Dimensions ◽  
Hydrodynamic Theory ◽  
Multiple Sources ◽  
Combined System ◽  
Lateral Lines

This research focuses on the signal processing required for a sensory system that can simultaneously localize multiple moving underwater objects in a three-dimensional (3D) volume by simulating the hydrodynamic flow caused by these objects. We propose a method for localization in a simulated setting based on an established hydrodynamic theory founded in fish lateral line organ research. Fish neurally concatenate the information of multiple sensors to localize sources. Similarly, we use the sampled fluid velocity via two parallel lateral lines to perform source localization in three dimensions in two steps. Using a convolutional neural network, we first estimate a two-dimensional image of the probability of a present source. Then we determine the position of each source, via an automated iterative 3D-aware algorithm. We study various neural network architectural designs and different ways of presenting the input to the neural network; multi-level amplified inputs and merged convolutional streams are shown to improve the imaging performance. Results show that the combined system can exhibit adequate 3D localization of multiple sources.

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