Paper Title:
Data Fusion of Probabilistic Full-Field Measurements for Material Characterization
  Abstract

This paper presents a data fusion technique to model more certain probabilistic full-field strain/displacement measurements for stochastic energy-based characterization proposed by the authors. The proposed technique measures the full-field measurements by using multiple cameras, constructing a Gaussian probability density function (PDF) for each camera, fusing the PDFs and developing the total PDF of the full-field measurements. Since the certainty of measurements is magnified by the use of multiple cameras, the use of multiple well-calibrated cameras could achieve the accuracy which no single camera could attain. The validity of the proposed energy-based characterization and its superiority to the original formulation were investigated using numerical analysis of an anisotropic material, and the proposed technique was found to improve the accuracy significantly with the addition of cameras.

  Info
Periodical
Key Engineering Materials (Volumes 462-463)
Edited by
Ahmad Kamal Ariffin, Shahrum Abdullah, Aidy Ali, Andanastuti Muchtar, Mariyam Jameelah Ghazali and Zainuddin Sajuri
Pages
686-691
DOI
10.4028/www.scientific.net/KEM.462-463.686
Citation
J. W. Pan, J. Q. Cheng, T. Furukawa, "Data Fusion of Probabilistic Full-Field Measurements for Material Characterization", Key Engineering Materials, Vols. 462-463, pp. 686-691, 2011
Online since
January 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Chun Ling Wu, Yong Feng Ju
Chapter 1: Transportation & Service Science
Abstract:In order to track the ballistic re-entry target, a new kind of ballistic target tracking algorithm, square-root quadrature Kalman filter...
99
Authors: Jing Mu, Chang Yuan Wang
Chapter 2: Manufacturing Technology
Abstract:We present the new filters named iterated cubature Kalman filter (ICKF). The ICKF is implemented easily and involves the iterate process for...
1329
Authors: Jun Du, Mei Sun, Liang Hua, Jia Sheng Ge, Ju Ping Gu
Chapter 6: Mechatronics
Abstract:In order to resolve the problem of seam tracking of the welding robots with unknown noise characteristics, a Weighted Multi-Sensor Data...
800
Authors: Hong Jiang Liu
Chapter 5: Control and Detection Technology
Abstract:In order to study the tracking problem of maneuvering image sequence target in complex environment with multi-sensor array, the adaptive...
906
Authors: Ya Lei Liu, Xiao Hui Gu
Chapter 2: Robotic, Automation, Sensors, Detection and Monitoring Technologies
Abstract:Abstract. In order to improve the tracking accuracy of 3D dynamic acoustic array to 2D maneuvering target in colored noise environment, the...
407