This work proposes the multilayered information fusion system MACRO
(multilayer attribute-based conflict-reducing observation) and the
µBalTLCS (fuzzified balanced two-layer conflict solving) fusion
algorithm to reduce the impact of conflicts on the fusion result. In
addition, a sensor defect detection method, which is based on the
continuous monitoring of sensor reliabilities, is presented. The
performances of the contributions are shown by their evaluation in the
scope of both a publicly available data set and a machine condition
monitoring application under laboratory conditions. Here, the MACRO
system yields the best results compared to state-of-the-art fusion
mechanisms.