This contribution deals with extraction and analysis of the transient component of a
deployable structure vibration based on the sparse decomposition with mixed norms. The …

Rolling element bearings are important parts of rotating machinery, and they are also one of
the most fault-prone parts in rotating machinery. Therefore, many new algorithms have been …

Compressive sensing (CS) is a newly developed data acquisition and processing technique
that takes advantage of the sparse structure in signals. Normally signals in their primitive …

In this paper, a novel decentralized modal identification method is proposed utilizing the
concepts of sparse blind source separation (BSS) and parallel factor decomposition. Unlike …

Sparse component analysis (SCA) has been introduced to the output-only modal
identification for several years. This paper proposes a new method based on hierarchical …

Sparse component analysis (SCA) approach was adopted to handle underdetermined blind
modal identification of structures, where the number of sensors is less than the number of …

Analysis and extraction of strongly frequency modulated signals have been a challenging
problem for adaptive data analysis methods, eg, empirical mode decomposition [NE Huang …

When structural dynamic design for smart control and health monitoring is executed,
imposed excitations on structures are one of most important issues in structural engineering …

Noise and non-stationary components may result in false boundaries when empirical
wavelet transform (EWT) is applied to mode decomposition. In this paper, a revised method …

In signal processing field, mode decomposition is one of the most important branches. Many
existing decomposition methods are mainly used to deal with narrow-band signals. If the …