scholarly journals Novel Detection Method for Consecutive DC Commutation Failure Based on Daubechies Wavelet with 2nd-Order Vanishing Moments

Energies ◽  
2018 ◽  
Vol 11 (2) ◽  
pp. 261 ◽  
Author(s):  
Tao Lin ◽  
Ziyu Guo ◽  
Liyong Wang ◽  
Rusi Chen ◽  
Ruyu Bi
Keyword(s):  
Detection Method ◽  
Daubechies Wavelet ◽  
Vanishing Moments ◽  
Commutation Failure

Arc-Fault Detection Method Research Based on Wavelet Transformation

2013 ◽  
Vol 646 ◽  
pp. 240-244
Author(s):  
Xin Jian Xiang ◽  
Zhang Lin
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Time Domain ◽  
Theoretical Basis ◽  
Wavelet Transformation ◽  
Detection Method ◽  
Frequency Domain Analysis ◽  
Daubechies Wavelet ◽  
Analysis Method ◽  
Protection Technology

The arc-fault is the main reason that cause electric fires. The technology of arc-fault circuit interrupters (AFCI) is the new circuit protection technology and it could avoid arc-fault causing fire effectively. The appearance of arc-fault can not be predicted. The traditional time domain or frequency domain analysis method for arc-fault signal processing is not ideal because it’s inaccurate and not in time. This paper bases on characteristics of arc-fault signals and analyzes the series connection arc-fault signal by Daubechies wavelet transform in 4 orders. As a result, it can provide the characteristics of arc-fault and detect arc-fault effectively and timely. This method is confirmed reliability by the simulation result and provides the theoretical basis of the development of AFCI.

scholarly journals Nonlinear Alleviation of Edge Effects in the Context of Minimizing Prediction Errors

2018 ◽  
Vol 10 (2) ◽  
pp. 161
Author(s):  
Monika Hadas-Dyduch
Keyword(s):  
Finite Elements ◽  
Wavelet Analysis ◽  
Edge Effects ◽  
Nonlinear Function ◽  
Innovative Approach ◽  
Prediction Errors ◽  
Daubechies Wavelet ◽  
Vanishing Moments ◽  
Filter Length ◽  
Orthogonal Wavelets

The aim of this article is to describe so-called “edge effects” in the context of wavelet analysis. The problem of “edge effects” is displayed in cases where the filter length is greater than 2. This is due to the fact that the calculation of the wavelet coefficients for the development of the last signal of finite elements, the filter - should theoretically move beyond the signal. The article describes different ways to solve this problem using an authored approach. One of the ways presented in the article is an innovative approach in terms of “edge effects”. The author’s proposal is based on the nonlinear function of the trend after the division of the series into smaller units. The results obtained show that in comparison with other methods, the author’s method reduces errors. In this article, the Daubechies wavelet was used for the study. The Daubechies wavelets are a family of orthogonal wavelets, characterized by a maximum number of vanishing moments for a given support.

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.

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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