Clamping force integrated computer aided tolerancing in composite assembly

2020 ◽  
pp. 002199832097102
Author(s):  
Hua Wang ◽  
Chen Yan ◽  
Junyang Yu ◽  
Kristina Wärmefjord
Keyword(s):  
Principal Component Analysis ◽  
Probability Distribution ◽  
Principal Component ◽  
Deformation Mode ◽  
Clamping Force ◽  
Fea Model ◽  
Computer Aided ◽  
Computational Aspects ◽  
Variation Simulation ◽  
Main Deformation

Traditional computer aided tolerancing method could not accomplish the tolerancing and variation simulation well in composite assembly. The paper presents a clamping force integrated computer aided tolerancing method for composite assembly. The stochastic variations and the stackup of variations are affected by clamping forces. The clamping force modified probability distribution is used to represent the modification based on the verified FEA model of the composite assembly. The clamping forces are coordinated based on the main deformation mode extracted by the principal component analysis to satisfy the coaxial tolerance requirements of the composite assembly. The assembly of an aircraft composite elevator is considered to illustrate the computational aspects of the proposed methods. The computer aided tolerancing method involving clamping forces outlined in the paper is found to be effective for composite assembly.

Compliant Assembly Variation Analysis Using Components Geometric Covariance

Manufacturing ◽  
2002 ◽  
Author(s):  
Jaime A. Camelio ◽  
S. Jack Hu
Keyword(s):  
Principal Component Analysis ◽  
Finite Element ◽  
Sheet Metal ◽  
Finite Element Methods ◽  
Principal Component ◽  
Deformation Mode ◽  
Component Analysis ◽  
Variation Analysis ◽  
The Individual ◽  
Sheet Metal Assembly

Dimensional variation is one of the most critical issues in the design of assembled products. This is especially important for the assembly of compliant, non-rigid parts since clamping and joining during assembly may introduce additional variation due to part deformation and springback. This paper presents a new methodology to predict sheet metal assembly variation using the components geometric covariance. The approach combines the use of principal component analysis and finite element methods to estimate the effect of components variation on assembly variation. Principal component analysis is applied to extract deformation patterns from production data, decomposing the component covariance in the individual contribution of these deformation “modes”. Finite element methods are used to determine the effect of each deformation “mode” over the assembly variation. The proposed methodology allows significant reduction in the computation effort required for variation analysis in sheet metal assembly. A case study is presented to illustrate the methodology.

scholarly journals MULTI LAYER PERCEPTRON DAN PRINCIPAL COMPONENT ANALYSIS UNTUK DIAGNOSA KANKER PAYUDARA

2018 ◽  
Vol 7 (1) ◽  
pp. 90
Author(s):  
Made Satria Wibawa ◽  
I Made Dendi Maysanjaya
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Computer Aided Diagnosis ◽  
Multi Layer Perceptron ◽  
Computer Aided ◽  
Aided Diagnosis

CAD (Computer Aided Diagnosis) merupakan teknik diagnosa berbantuan komputer untuk meningkatkan akurasi hasil diagnosa dari suatu penyakit. CAD telah banyak digunakan untuk diagnosa dari berbagai penyakit, khususnya penyakit kanker payudara. Multi layer perceptron (MLP) sebagai salah metode dari jaringan saraf tiruan telah banyak digunakan untuk klasifikasi kanker payudara. Penelitian ini bertujuan untuk mencari kombinasi parameter paling optimal untuk mendiagnosa kanker payudara. Kombinasi parameter tersebut juga diujikan dengan metode reduksi fitur Principal Component Analysis (PCA). Hasil penelitian menunjukkan bahwa parameter paling optimal adalah fungsi optimisasi RELU serta TANH dengan fitur optimisasi adam dengan tingkat akurasi 0.973

Conformational analysis of spiro-epoxides by principal component analysis of molecular dynamics trajectories

2017 ◽  
Vol 19 (47) ◽  
pp. 31706-31713 ◽  
Author(s):  
T. Hrenar ◽  
I. Primožič ◽  
D. Fijan ◽  
M. Majerić Elenkov
Keyword(s):  
Molecular Dynamics ◽  
Principal Component Analysis ◽  
Probability Distribution ◽  
Conformational Analysis ◽  
Molecular Dynamics Simulations ◽  
Principal Component ◽  
Component Analysis ◽  
Coordinate Space ◽  
Dynamics Simulations

A probability distribution calculated in a reduced internal coordinate space sampled by molecular dynamics simulations for spiro-epoxide derivatives.

Construction of Digital Statistical Atlases of the Liver and their Applications to Computer-Aided Diagnosis

2012 ◽  
pp. 68-79
Author(s):  
Yen-Wei Chen
Keyword(s):  
Principal Component Analysis ◽  
Medical Image Analysis ◽  
Principal Component ◽  
Hepatic Disease ◽  
Human Anatomy ◽  
Liver Segmentation ◽  
Volume Analysis ◽  
Computer Aided ◽  
Voxel Intensity ◽  
Aided Diagnosis

Digital atlases of the human anatomy are a new and hot topic in medical image analysis. The basic idea of the digital atlas is to capture the variability of an organ’s location, shape, and voxel intensity (texture) from a training set. In this chapter, the authors present current progress toward constructing digital atlases of the liver and their applications to liver segmentation and diagnosis of hepatic disease. They also introduce a new mathematic framework (generalized N-dimensional principal component analysis) based on multi-linear algebra for medical volume analysis.

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