Diagnostic Information Fusion for Manufacturing Processes

This paper addresses diagnostic information fusion for situations where several diagnostic tools are used to estimate a single system state. These estimates will always disagree to some extent and it is the task of the fusion module to provide an estimate which is more reliable than the best of the diagnostic tools. To that end, a fusion process was developed which performs a weighted average of individual tools using confidence values assigned dynamically to the individual diagnostic tools. These confidence values are derived from validation curves which are designed using individual a priori tool information and which are centered about the previous system estimate. In a further step, the fusion output is smoothed leading to additional performance improvement. In experiments, data were gathered from a high speed milling machine and fed through several developed diagnostic tools.