Sentence examples for modal identification method from inspiring English sources

This paper proposes a new modal identification method of ambient vibration responses.

Then the cross-correlation function is taken as the initial input signal to identify parameters with modal identification method in time domain.

Significant conclusions about the complicated vibration processes composed of nonstationary and intrinsic modal terms are drawn by using the proposed empirical modeless decomposition and modal identification method.

However, the high-quality vibration data collection technology calls for a more accurate modal identification method to improve the accuracy of the results.

Traditional natural excitation technique uses cross-correlation function that responses between two points to replace impulse response function, identifying parameters with time domain modal identification method.

The study presented here focuses on implementation of an integrated modal identification method in time domain allowing the monitoring of mode shapes.

Therefore, this method combines the advantages of the two existing modal identification methods and overcomes some of their limitations.

Existing BSS modal identification methods, however, require the number of sensors at least equal to that of sources (active modes).

In the existing modal identification methods for forced vibration, it is generally assumed that the forced vibration response dominates the measurement data and the influence of the ambient vibration response is ignored.

The main novelties of this work involve the new formulation in frequency-scale domain and the capacity for the identification of modal parameters without the step of ridges extraction in comparison with previous wavelet-based modal identification methods.

The numerical analysis results show that the proposed modal parameter identification method based on HJAD technology not only has the advantage of a traditional blind modal parameter identification algorithm, but can also overcome the limitation of not being able to estimate more active modes than the number of available sensors.