Perceptron, Inc.

Hannes Loferer

Dale R Greer

Richard Krakowski

Jim Roan

Yu Guo

Jiri Gardavsky

A system and method for identifying significant bivariate checkpoints. The system includes a controller configured to receive measurements for a plurality of checkpoints and calculate the covariance and correlation for each checkpoint pair. The controller identifies significant bivariate checkpoints based on the covariance between the checkpoint pairs. Further, the controller may also calculate the correlation for each checkpoint pair and identify the significant bivariate checkpoints based on a combination of the covariance and the correlation between the checkpoints. Further, the controller may rank the significant bivariate checkpoints and provide the significant bivariate checkpoints to a principal component algorithm.

Structural data analysis system

An improved target assembly is provided for use in calibrating a non-contact sensor in a sensor calibration system. The target assembly includes: a plate member; three pairs of truncated cones mounted adjacent to each other on a surface of the plate member, where one of the truncated cones in each pair is orientated inversely in relation to the other truncated cone; and at least three targets connected to the plate member for calibrating the target assembly in relation to a reference frame external to the target assembly.

Growing community of inventors

Ann Arbor, MI, United States of America

Hannes Loferer