Physical Sciences and Mathematics Commons^™

A Novel Method For Intelligent Single Fault Detection Of Bearings Using Sae And Improved D–S Evidence Theory, Jianguang Lu, Huan Zhang, Xianghong Tang

Computer Science Faculty Publications and Presentations

In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Encoder (SAE) and results fusion of improved Dempster–Shafer evidence theory (D–S). Multi-fault signal compression features of bearings were extracted by SAE on multiple vibration sensors’ data. Data sets were constructed by the extracted compression features to train the Support Vector Machine (SVM) according to the rule of single fault detection (R-SFD) this paper proposed. Fault detection results were obtained by the improved D–S evidence theory, …