Sentence examples for estimating the mode from inspiring English sources

Figure 2 ARMA-P method for estimating the mode shape information based on ambient signals.

The algorithm proposed in this article shows great promise for estimating the mode shape properties of power systems.

This method works well in estimating the mode shape information of multiple oscillation modes simultaneously based on ambient signals with different SNR value.

The ARMA-P method performs well in estimating the mode shape of multiple modes simultaneously based on actual ambient signals in China Southern Power Grid.

This category of methods locates the oscillation source by estimating the mode shape using measurements from different locations and then identifies the source based on the mode shape.

A methodology considering the model order selection called ARMA-P, used for estimating the mode shape properties from time-synchronized phasor measurements, is presented.

In contrast to the traditional Prony and EKF methods for estimating the modes parameters, which require the order of the model and the initial parameters of the mode, the hybrid Prony-cross-correlation does not require any previous information.

We estimate the mode by maximization over the curve estimator, which is given as a weighted mean of the observations, including most of the common kernel estimators, such as Gasser Müller, Priestley Chao and Nadaraya Watson.

To estimate the mode accurately, it is important to study the impact of forced oscillations on mode estimation.

The results demonstrate that the new ARMA-P method can effectively estimate the mode shape properties from ambient data.

To obtain the complete mode shapes, an interpolation method was developed to estimate the mode shape values for the locations without measurements.