Multisensor process performance assessment through use of autoregressive modeling and feature maps

This paper presents an algorithm for quantitative assessment of process or machine performance. The algorithm is based on the fusion of multiple sensor inputs and matching of the currently observed system signatures against those observed during its normal behavior. In contrast to traditional monitoring techniques, neither faulty data nor historical data are needed for the performance assessment to be made. This quantitative information about process performance can be used to take appropriate maintenance action in a timely manner. Effectiveness of the methods presented in this paper was experimentally demonstrated in multisensor welding process assessment.