Research on Bearing Fault Diagnosis based on Information Fusion
杨永生 YANG Yong-sheng · OME Information · 2011
Much useful information obtained from multi-sensors can not be used efficiently in the bear faults diagnosis. An information fusion model is proposed in this paper to solve the problem. In this model, information obtained from multi-sensors is integrated by different weights assigned in the sensors. Through using in a bear fault diagnosis example, this model is confirmed with certain superiority in classification precision and performance of popularizing.