By Topic

A Pattern Recognition Technique for System Error Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hankley, William J. ; Division of Computer Science, University of Utah, Salt Lake City, Utah. ; Merrill, Hyde M.

The error analysis problem is the resolving of a limited set of measurements in terms of a large set of possible but improbable physical errors. The relation between the measurements and the errors is modeled in part as a set of linear undetermined equations ¿v = A¿r, where ¿v is a vector of the measurements and ¿r is a vector of error parameters, and in part by specification of the relations between the parameters ¿ri and the physical errors. An approximate solution to the model equations is deemed physically reasonable if it reflects one or only a few of the physical errors. To evaluate a candidate solution consisting of ¿r and its interpretation as physical errors, we introduce a criterion function ¿ = ¿0 + ¿1; ¿0 is a measure of ¿¿v - A¿r¿ and ¿1 is a measure of the likelihood of the composite physical error associated with ¿r. With this criterion, the common least-squares (pseudoinverse) solution of the model equations is shown to be inadequate (it minimizes ¿0 but not ¿). A pattern recognition technique is presented and shown to yield solutions that are both numerically and physically reasonable, i.e., both ¿0 and ¿1 are small. The technique is illustrated by application to miscalibration analysis using an inertial guidance system model.

Published in:

Reliability, IEEE Transactions on  (Volume:R-20 ,  Issue: 3 )