Condition Monitoring Of Drive Trains By Data Fusion Of Acoustic Emission And Vibration Sensors

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. The data analysis can be improved by applying machine learning algorithms and fusion of data from heterogenous sensors. This paper presents an approach for a step-wise integration of classifications gained from vibration and ac... » read more