scholarly journals Voltage Harmonic and Interharmonic Detection Method for DC Microgrid based on Hanning Window Interpolation

2019 ◽  
Vol 1346 ◽  
pp. 012020
Author(s):  
ZHU Hanlin ◽  
TIAN Lijun ◽  
QI Dayong ◽  
GAO Hui
Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2452
Author(s):  
Matthew Davidson ◽  
Andrea Benigni

This paper provides a simple low-level unidirectional global communication method for DC microgrids, and requires no hardware modifications to the microgrid and interfacing power electronic converters. The underlying premise to this communication method is injecting low-frequency low-voltage sinusoidal components into the DC microgrid power lines. This method deviates from the common bit-level communication scheme by relating parameters and commands with certain frequency components. Communication structures are included as a basis for communication protocols, and a detection method is proposed for detecting the injected frequencies. The injection method, communication structure, and detection method are implemented on a live-scale DC microgrid.


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