NDLI: Fault Diagnosis of Rotating System based on Multi-sensor Data Fusion

Content Provider	IEEE Xplore Digital Library
Author	Jian Li Zhaohui Zhang Yanjun Fang Bo Xi
Copyright Year	2006
Description	Author affiliation: Meas. Technol. & Syst. Lab, Nanjing Normal Univ. (Jian Li; Zhaohui Zhang)
Abstract	This paper deals with a multi-sensor system applied to mechanical fault diagnosing fusion pattern based on neural network, the veracity of diagnosis system can be increased greatly. The methods for data fusion architecture and construction of the neural network are given. Data preprocessing and features extraction have been done by using ICA (independent component analysis) method. Multi-sensor information fusion and controller expert fuzzy neural networks are proposed for data relation construct. Applying the redundancy technology and multi-sensor information fusion technology, the synchronized automated data processing and malfunction warning could be realized based on fusion system. Experiments are given showing the effectiveness of the proposed hierarchical intelligent control system
Starting Page	5466
Ending Page	5470
File Size	147292
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1714117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Neural networks Independent component analysis Data preprocessing Feature extraction Automatic control Fuzzy neural networks Fuzzy control Redundancy Data processing Multi-sensor Information fusion ICA Fault diagnoses
Content Type	Text
Resource Type	Article

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