Smooth orthogonal decomposition-based vibration mode identification

2006 ◽  
Vol 292 (3-5) ◽  
pp. 461-473 ◽  
Author(s):  
David Chelidze ◽  
Wenliang Zhou
Keyword(s):  
Vibration Mode ◽  
Orthogonal Decomposition ◽  
Mode Identification ◽  
Smooth Orthogonal Decomposition

Nonlinear Smooth Orthogonal Decomposition of Kinematic Features of Sawing Reconstructs Muscle Fatigue Evolution as Indicated by Electromyography

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
David B. Segala ◽  
Deanna H. Gates ◽  
Jonathan B. Dingwell ◽  
David Chelidze
Keyword(s):  
Muscle Fatigue ◽  
Fixed Number ◽  
Orthogonal Decomposition ◽  
Muscle Injuries ◽  
Individual Muscle ◽  
Dimensional Reconstruction ◽  
Order Of Magnitude ◽  
Muscle Groups ◽  
The Right ◽  
Smooth Orthogonal Decomposition

Tracking or predicting physiological fatigue is important for developing more robust training protocols and better energy supplements and/or reducing muscle injuries. Current methodologies are usually impractical and/or invasive and may not be realizable outside of laboratory settings. It was recently demonstrated that smooth orthogonal decomposition (SOD) of phase space warping (PSW) features of motion kinematics can identify fatigue in individual muscle groups. We hypothesize that a nonlinear extension of SOD will identify more optimal fatigue coordinates and provide a lower-dimensional reconstruction of local fatigue dynamics than the linear SOD. Both linear and nonlinear SODs were applied to PSW features estimated from measured kinematics to reconstruct muscle fatigue dynamics in subjects performing a sawing motion. Ten healthy young right-handed subjects pushed a weighted handle back and forth until voluntary exhaustion. Three sets of joint kinematic angles were measured from the right upper extremity in addition to surface electromyography (EMG) recordings. The SOD coordinates of kinematic PSW features were compared against independently measured fatigue markers (i.e., mean and median EMG spectrum frequencies of individual muscle groups). This comparison was based on a least-squares linear fit of a fixed number of the dominant SOD coordinates to the appropriate local fatigue markers. Between subject variability showed that at most four to five nonlinear SOD coordinates were needed to reconstruct fatigue in local muscle groups, while on average 15 coordinates were needed for the linear SOD. Thus, the nonlinear coordinates provided a one-order-of-magnitude improvement over the linear ones.

Evaluation of Material Properties of CFRP Plate by Vibration Mode Identification

2017 ◽  
Vol 2017 (0) ◽  
pp. 344
Author(s):  
Hisayoshi EBINA ◽  
Hiroki MATSUMOTO ◽  
Akira HARADA ◽  
Yoshiki OHTA ◽  
Shinya HONDA
Keyword(s):  
Material Properties ◽  
Vibration Mode ◽  
Mode Identification ◽  
Cfrp Plate

Modal Analysis With Smooth Karhunen-Loe`ve Decomposition

2009 ◽  
Author(s):  
S. Bellizzi ◽  
Rubens Sampaio
Keyword(s):  
Random Field ◽  
Modal Analysis ◽  
Covariance Matrix ◽  
Random Fields ◽  
Time Derivative ◽  
Normal Modes ◽  
Orthogonal Decomposition ◽  
White Noise Excitation ◽  
Smooth Orthogonal Decomposition ◽  
Vibrating Systems

In this paper, the Smooth Orthogonal Decomposition is formulated in term of a Smooth Karhunen-Loe`ve Decomposition (SKLD) to analyze random fields. The SKLD is obtained solving a generalized eigenproblem defined from the covariance matrix of the random field and the covariance matrix of the associated time derivative random field. The main properties of the SKLD are described and compared to the classical Karhunen-Loe`ve decomposition. The SKLD is then applied to the responses of randomly excited vibrating systems with a view to performing modal analysis. The associated SKLD characteristics are interpreted in case of linear vibrating systems subjected to white noise excitation in terms of normal modes. Discrete and continuous mechanical systems are considered in this study.

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