Study Of Vertical Emulsifier Fault Diagnosis System Based On EMD-Sample Entropy And BP Neural Network
Yue-sheng Wang, Yao-wen Sun
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.103How to use a DOI?
- Emulsifier, Sample Entropy, EMD, BP Neural Network.
- Aiming at the nonlinear characteristics of the fault vibration signal of the emulsifier, a feature extraction method based on Empirical Mode Decomposition (EMD) and Sample Entropy (SampEn) is proposed.In this method, the original vibration signal is decomposed into a finite number of intrinsic mode functions by EMD, then we select the Sample Entropy (SampEn) of the intrinsic mode function which contains the main failure information as the characteristic parameter, and BP neural network is used to diagnose the faults of the emulsifier in this study. Experiments verified that the BP neural network diagnosis method can get better fault diagnosis effect by using the EMD pretreatment to extract the Sample Entropy as the characteristic parameter.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yue-sheng Wang AU - Yao-wen Sun PY - 2016/09 DA - 2016/09 TI - Study Of Vertical Emulsifier Fault Diagnosis System Based On EMD-Sample Entropy And BP Neural Network BT - 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016) PB - Atlantis Press SP - 519 EP - 523 SN - 2352-538X UR - https://doi.org/10.2991/amitp-16.2016.103 DO - https://doi.org/10.2991/amitp-16.2016.103 ID - Wang2016/09 ER -