Spacing detection method for shearing interference fringes containing speckle noises

2020 ◽  
Author(s):  
Shuman He ◽  
Chenguang Cai ◽  
Zhihua Liu ◽  
Ying Wang ◽  
Huichao Shi
Keyword(s):  
Detection Method ◽  
Interference Fringes ◽  
Shearing Interference

Detection of Laser Direction and Wavelength Using the Unitized Wedge

2011 ◽  
Vol 255-260 ◽  
pp. 2155-2158
Author(s):  
Li Zhang
Keyword(s):  
Detection Method ◽  
Optical Path Difference ◽  
Path Difference ◽  
Optical Path ◽  
Interference Fringes ◽  
Random Direction ◽  
Array Camera

A novel detection method of laser direction and wavelength synchronal is fabricated by combining the four wedges and CMOS array camera. The unitized wedges we designed are composed of the four same wedges, and the joint is non-transparent. When the laser incident in the random direction, we calculate the distance of interference fringes in the four wedges, and deduce laser direction and wavelength. By simulation, it generates the drawings of optical path difference and the mini-distance when the minimum identification angle is 1o. In experiment, when we choose the angle of wedge is 0.01rad (≈0.57o), the distance of interference fringes is 10μm, larger than 8μm in CMOS array camera, so the interference fringes with the 532nm laser can be detected.

Solid-phase immunoelectron microscopy for rapid diagnosis of enteroviruses

1984 ◽  
Vol 42 ◽  
pp. 226-227 ◽  
Author(s):  
K. Pegg-Feige ◽  
F. W. Doane
Keyword(s):  
Electron Microscopy ◽  
Cell Culture ◽  
Immunoelectron Microscopy ◽  
Detection Method ◽  
Solid Phase ◽  
Protein A ◽  
Plant Viruses ◽  
Rapid Diagnosis ◽  
Virus Diagnosis ◽  
Antiviral Antibody

Immunoelectron microscopy (IEM) applied to rapid virus diagnosis offers a more sensitive detection method than direct electron microscopy (DEM), and can also be used to serotype viruses. One of several IEM techniques is that introduced by Derrick in 1972, in which antiviral antibody is attached to the support film of an EM specimen grid. Originally developed for plant viruses, it has recently been applied to several animal viruses, especially rotaviruses. We have investigated the use of this solid phase IEM technique (SPIEM) in detecting and identifying enteroviruses (in the form of crude cell culture isolates), and have compared it with a modified “SPIEM-SPA” method in which grids are coated with protein A from Staphylococcus aureus prior to exposure to antiserum.

Quanitative aspects of electron diffraction using electron holography

1995 ◽  
Vol 53 ◽  
pp. 616-617
Author(s):  
E. Völkl ◽  
L.F. Allard ◽  
B. Frost ◽  
T.A. Nolan
Keyword(s):  
Electron Beam ◽  
Electron Diffraction ◽  
Software Package ◽  
Spatial Coherence ◽  
Electron Holography ◽  
Image Intensity ◽  
Interference Fringes ◽  
Complex Image ◽  
The Difference ◽  
Recorded Image

Off-axis electron holography has the well known ability to preserve the complex image wave within the final, recorded image. This final image described by I(x,y) = I(r) contains contributions from the image intensity of the elastically scattered electrons IeI (r) = |A(r) exp (iΦ(r)) |, the contributions from the inelastically scattered electrons IineI (r), and the complex image wave Ψ = A(r) exp(iΦ(r)) as:(1) I(r) = IeI (r) + Iinel (r) + μ A(r) cos(2π Δk r + Φ(r))where the constant μ describes the contrast of the interference fringes which are related to the spatial coherence of the electron beam, and Φk is the resulting vector of the difference of the wavefront vectors of the two overlaping beams. Using a software package like HoloWorks, the complex image wave Ψ can be extracted.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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