Intercomparisons of Site VSWR Measurement Methods using Mode Filtering, Time Domain and Spatial Sampling Techniques

Author(s):  
Zhong Chen ◽  
Stuart Gregson
2006 ◽  
pp. 317-347 ◽  
Author(s):  
Christof Huebner ◽  
Stefan Schlaeger ◽  
Rolf Becker ◽  
Alexander Scheuermann ◽  
Alexander Brandelik ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4166 ◽  
Author(s):  
Bin Liu ◽  
Tingzhang Liu ◽  
Jianfei Zhao

In this paper, a wavenumber–searching method based on time-domain compensation is proposed to obtain the wavenumber of the Lamb wave array received signal. In the proposed method, the time-domain sampling signal of the linear piezoelectric transducer (PZT) sensor array is converted into a spatial sampling signal using the searching wavenumber. The two–dimensional time-spatial-domain Lamb wave received signal of the linear PZT sensor array is then converted into a one-dimensional synthesized spatial sampling signal. Further, the sum of squared errors between the synthesized spatial sampling signal and its Morlet wavelet fitting signal is calculated at each searching wavenumber. Finally, the wavenumber of the Lamb wave array received signal is obtained as the searching wavenumber corresponding to the minimum error. This method was validated on a 2024-T3 aluminum alloy. The validation results showed that the proposed method can successfully obtain the wavenumber of the Lamb wave array received signal, whose spatial sampling rate does not satisfy the Nyquist sampling theorem; the wavenumber error does not exceed 2.2 rad/m. Damage localization based on the proposed method was also validated on a carbon fiber composite laminate plate, and the maximum damage localization error was no more than 2.11 cm.


2014 ◽  
Vol 14 (5) ◽  
pp. 270-278 ◽  
Author(s):  
P. Sovilj ◽  
M. Milovanović ◽  
D. Pejić ◽  
M. Urekar ◽  
Z. Mitrović

Abstract Measurement methods, based on the approach named Digital Stochastic Measurement, have been introduced, and several prototype and small-series commercial instruments have been developed based on these methods. These methods have been mostly investigated for various types of stationary signals, but also for non-stationary signals. This paper presents, analyzes and discusses digital stochastic measurement of electroencephalography (EEG) signal in the time domain, emphasizing the problem of influence of the Wilbraham-Gibbs phenomenon. The increase of measurement error, related to the Wilbraham-Gibbs phenomenon, is found. If the EEG signal is measured and measurement interval is 20 ms wide, the average maximal error relative to the range of input signal is 16.84 %. If the measurement interval is extended to 2s, the average maximal error relative to the range of input signal is significantly lowered - down to 1.37 %. Absolute errors are compared with the error limit recommended by Organisation Internationale de Métrologie Légale (OIML) and with the quantization steps of the advanced EEG instruments with 24-bit A/D conversion


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