Bitumen and bituminous binders. Determination of equiviscous temperature based on low shear viscosity using a dynamic shear rheometer in low frequency oscillation mode

2008 ◽  
Keyword(s):  
Shear Viscosity ◽  
Oscillation Mode ◽  
Low Frequency ◽  
Dynamic Shear ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Bituminous Binders ◽  
Low Shear Viscosity ◽  
Low Shear

Identification the Low-Frequency Oscillation Stakeout of Power System by Wide-Area Measurement System

2011 ◽  
Vol 128-129 ◽  
pp. 594-601
Author(s):  
Yang Liu ◽  
Qian Huang ◽  
Dong Chen
Keyword(s):  
Power System ◽  
Measurement System ◽  
Rapid Development ◽  
Oscillation Mode ◽  
Low Frequency ◽  
Area Measurement ◽  
Wide Area ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Wide Area Measurement System

With the rapid development of interconnected power grid, the phenomenon of power system low-frequency oscillation appears unavoidably. Then, the appearance of wide-area measurement system provided a supporting technology for better scout low-frequency oscillation system and better recognize the oscillation mode . In this paper, the existing oscillation mode identifying methods are analyzed from the viewpoint of calculation speed, criterion, calculation accuracy, etc. Mainly compared the applicability of two methods, Prony and ESPRIT . Based on the above research, a new idea of monitoring power system low frequency oscillation based on WAMS is put forward in this paper.

Smoothness Prior Approach to Removing Nonlinear Trends from Signals in Identification of Low Frequency Oscillation Mode

2014 ◽  
Vol 672-674 ◽  
pp. 1070-1074
Author(s):  
Yu Jiang Wang ◽  
Jian Li ◽  
Hui Xu ◽  
Hai Ou Yan ◽  
Jia Yuan ◽  
...  
Keyword(s):  
Regularization Parameter ◽  
Oscillation Mode ◽  
Low Frequency ◽  
Filter Method ◽  
Measured Signal ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Mode Identification ◽  
Nonlinear Trend ◽  
Nonlinear Trends

The online identification of low frequency oscillation mode based on measured signal from PMU is the base of damping control. Removing nonlinear trend from the signal effectively can ensure the precision of mode identification. A method named smoothness prior approach (SPA) is proposed to remove the nonlinear trend from measured signal. In order to meet the demand of removing nonlinear trend for identification of low frequency oscillation based on analyzing the basic principle of smoothness prior approach, it determines regularization parameter of smoothness prior approach according to its characteristic of frequency response. It is used to analyze the simulation signals from IEEE-39 bus power system and the measured signals in some power grid, and compared with empirical mode decomposition and digital filter method. The results demonstrate that this proposed method can successfully remove nonlinear trend from the signal and improve the speed of computation, as well as the precision of mode identification, which has a relatively high practical value.

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