Composite Fault Diagnosis and Intelligent Maintenance Based on Data Driven

Abstract:

For composite fault is difficult to diagnose, the characteristics of the large amount of data. This paper presents a method of The Prediction method of Composite Fault Based on data driven to establish intelligence unit Based on a collection of virtual individuals associated with the virtual failure associated collection and virtual behavior associated collection. Composite fault warning engine modeling is proposed, and give the warning value of composite fault finally. This method is fully assessing the future "dominant state" on the basis of the fully aware of current "hidden state". The impact of factors such as disturbance of hidden failures on composite fault prediction are fully considered, to some extent, the long-span composite failure prediction problem is solved, and the experiments show that the method effectively increases the accuracy of composite fault prediction.

• Periodical: Key Engineering Materials (Volume 693)
• Pages: 1357-1360
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.693.1357
• Online since: May 2016
• Authors: Jing Liu, Yong Feng Dong, Yan Li, Si Yuan Lei, Shu Qun He
• Keywords: Big Data Driven, Composite Fault, Data Modeling, Fault Diagnosis, Hidden Fault

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