Force Identification from Structural Response

Abstract

Force identification is a type of system identification procedure which determines applied forces from system response measurements. To identify the force, one can consider the system model and known parameters, and then use the measured response to determine the unknown forces. This report proposes a more direct way to identify the unknown force without knowing the model of the system. This approach, called the sum of weighted acceleration technique (SWAT), can predict input forces with measured linear and nonlinear structural responses. SWAT uses measured accelerations multiplied by effective or optimal weights to estimate the input force. The effective weights are the coefficients of an equivalent mass at each acceleration location, and once they are determined, the unknown input forces can be predicted by a mathematical formulation--the goal of force identification. The approach of SWAT was (1) validated in the time and frequency domain, and (2) for practical applications, extended to a finite element approach for further validation of larger elastic structures. Results show that the force calculated from SWAT accurately predicted the force inputted to the structure. Keywords: Force identification, Dynamic loads, System identification, Inverse problem, Force mapping.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1990
Accession Number
ADA221003

Entities

People

  • T. J. Kreitinger

Tags

Communities of Interest

  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Science
  • Computers
  • Differential Equations
  • Engineering
  • Equations
  • Finite Element Analysis
  • Frequency Domain
  • Inverse Problems
  • Linear Systems
  • Literature Surveys
  • Modal Analysis
  • Nonlinear Systems
  • Personal Computers
  • Strain Gages
  • United States

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Research.
  • Computational Modeling and Simulation