A CNN-based shock detection method in flow visualization

2019 ◽  
Vol 184 ◽  
pp. 1-9 ◽  
Author(s):  
Yang Liu ◽  
Yutong Lu ◽  
Yueqing Wang ◽  
Dong Sun ◽  
Liang Deng ◽  
...  
2012 ◽  
Vol 271-272 ◽  
pp. 372-377
Author(s):  
Bin Bin Yu ◽  
Jun Tang Yuan

Bonding strength of the interface of film-substratum is an important factor and key problem that influence the reliability and usage of film-substratum system. The new technology of pulsed-laser shock detection method which analyzes the mechanism and mathematical model of film separation under the action of pulsed-laser shock,. With the example of measuring the adhesion strength of TiN/SKD11 film system, the surface was respectively impacted with pulsed-laser at the range of 650~1000mJ. To observe the surface topography of Impact points by scanning electron microscope, and to identify TiN film failure threshold by the reflected signal detection. By analyzing the experimental result, it was suggested that film/substrate interfacial adhesion strength was 4.954GW/cm2.


Author(s):  
K. Pegg-Feige ◽  
F. W. Doane

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.


Author(s):  
Weihai Sun ◽  
Lemei Han

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.


Sign in / Sign up

Export Citation Format

Share Document