Open AccessMechatronics Fault Prediction and Diagnosis Based on Multi Sensor Information Fusion
Author(s) -
Jinghua Yu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1982/1/012100
Subject(s) - sensor fusion , fault (geology) , mechatronics , feature (linguistics) , data mining , information fusion , artificial intelligence , fusion , computer science , pattern recognition (psychology) , fuse (electrical) , engineering , machine learning , linguistics , philosophy , seismology , electrical engineering , geology
This paper studies the mechatronics fault prediction and diagnosis based on multi-sensor information fusion. According to the method of data fusion, the fault diagnosis system is divided into data level fusion module, feature level fusion module and decision level fusion module. The data level fusion module mainly processes the measured signals of multi-sensor to extract the feature information of fault diagnosis. The feature level fusion module uses three parallel neural networks with the same structure. In this paper, the basic probability assignment method of decision level D-S evidence theory is used as the basic algorithm of data processing. The decision-making level uses the method of D-S evidence theory to fuse the results of feature level local diagnosis to get the final diagnosis result. The experimental data show that the accuracy and efficiency of the proposed Mechatronics fault prediction and diagnosis system based on multi-sensor information fusion can meet the requirements of engineering technology.