Statistical moment analysis of multi-degree of freedom dynamic system based on polynomial dimensional decomposition method

2018 ◽  
Vol 93 (4) ◽  
pp. 2003-2018 ◽  
Author(s):  
Kuan Lu
Keyword(s):  
Dynamic System ◽  
Decomposition Method ◽  
Statistical Moment ◽  
Degree Of Freedom ◽  
Moment Analysis ◽  
Statistical Moment Analysis ◽  
Dimensional Decomposition ◽  
Polynomial Dimensional Decomposition

Interaction of surfactants with poly(acryloyl-l-proline methyl ester) gel and its statistical moment analysis

1995 ◽  
Vol 46 (2) ◽  
pp. 181-183 ◽  
Author(s):  
Masaru Yoshida ◽  
Agneza Safranj ◽  
Hideki Omichi ◽  
Masaharu Miyajima ◽  
Ryoichi Katakai
Keyword(s):  
Methyl Ester ◽  
Statistical Moment ◽  
Moment Analysis ◽  
Statistical Moment Analysis

New Statistical Moments for Diagnostics of Rolling Element Bearings

1997 ◽  
Vol 119 (3) ◽  
pp. 425-432 ◽  
Author(s):  
F. Honarvar ◽  
H. R. Martin
Keyword(s):  
Statistical Moment ◽  
Moment Analysis ◽  
Statistical Moments ◽  
Rolling Element Bearings ◽  
Effective Technique ◽  
The Third ◽  
Statistical Moment Analysis ◽  
Rolling Element ◽  
Major Parameter ◽  
Central Statistical

Statistical moment analysis has proven to be a very effective technique for diagnosis of rolling element bearings. The fourth normalized central statistical moment, kurtosis, has been the major parameter in this method. In this paper it will be shown that the third normalized statistical moment can be as effective as kurtosis if the data is initially rectified. The advantage of this moment over the traditional kurtosis value is its lesser susceptibility to spurious vibrations, which is considered to be one of the shortcomings of higher statistical moments including kurtosis. The sensitivity of this moment to changes of load and speed is also less than kurtosis. The proposed method can also be applied to higher odd statistical moments.

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