Estimation of the weight distribution function of a complex object for portion control in an innovative can filling system

1997 ◽  
Author(s):  
F. Omar ◽  
C.W. de Silva
Keyword(s):  
Distribution Function ◽  
Weight Distribution ◽  
Complex Object ◽  
Portion Control ◽  
Filling System

Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel

2021 ◽  
pp. 147592172110339
Author(s):  
Guoqiang Liu ◽  
Binwen Wang ◽  
Li Wang ◽  
Yu Yang ◽  
Xiaguang Wang
Keyword(s):  
Distribution Function ◽  
Diagnostic Imaging ◽  
Weight Distribution ◽  
Composite Structures ◽  
Damage Identification ◽  
Guided Wave ◽  
Composite Panel ◽  
Damage Localization ◽  
Localization Accuracy ◽  
Direct Interpretation

Due to no requirement for direct interpretation of the guided wave signal, probability-based diagnostic imaging (PDI) algorithm is especially suitable for damage identification of complex composite structures. However, the weight distribution function of PDI algorithm is relatively inaccurate. It can reduce the damage localization accuracy. In order to improve the damage localization accuracy, an improved PDI algorithm is proposed. In the proposed algorithm, the weight distribution function is corrected by the acquired relative distances from defects to all actuator–sensor pairs and the reduction of the weight distribution areas. The validity of the proposed algorithm is assessed by identifying damages at different locations on a stiffened composite panel. The results show that the proposed algorithm can identify damage of a stiffened composite panel accurately.

RANKING FUZZY NUMBERS USING α-WEIGHTED VALUATIONS

2000 ◽  
Vol 08 (05) ◽  
pp. 573-591 ◽  
Author(s):  
MARCIN DETYNIECKI ◽  
RONALD R. YAGER
Keyword(s):  
Distribution Function ◽  
Weight Distribution ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Ranking Method ◽  
Valuation Method

We studied here on some simple examples the interaction between valuation family, parameters and ranking result. The ranking method studied is based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. The valuation method considered was introduced initially by the Yager and Filev. This valuation consists in the integration over α-levels, of the average of each α-cut weighted by a weight distribution function. We finish by introducing a new weight distribution function.

KLAUDER–PERELOMOV AND GAZEAU–KLAUDER COHERENT STATES FOR SOME SHAPE INVARIANT POTENTIALS

2002 ◽  
Vol 17 (26) ◽  
pp. 1701-1712 ◽  
Author(s):  
A. CHENAGHLOU ◽  
H. FAKHRI
Keyword(s):  
Distribution Function ◽  
Weight Distribution ◽  
Coherent States ◽  
Mandel Parameter ◽  
Shape Invariance ◽  
Shape Invariant ◽  
Quantum Models ◽  
Invariance Theory ◽  
Poissonian Statistics

Firstly, the solvability of some quantum models like Eckart and Rosen–Morse II are explained on the basis of the shape invariance theory. Then, two generalized types of the Klauder–Perelomov and Gazeau–Klauder coherent states are calculated for the models. By means of calculating the Mandel parameter, it is shown that the weight distribution function of the first type coherent states obeys the Poissonian and super-Poissonian statistics, however, the weight distribution function of the second type coherent states obeys the Poissonian and sub-Poissonian statistics.

Sign in / Sign up

Export Citation Format

Share Document