Research and Application of Equipment Fault Diagnosis Based on Cloud Computing

Guang Lei Li; Shu Min Sun; Qing Bo Mao

doi:10.4028/www.scientific.net/AMR.706-708.1898

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Implementing Sparse Matrix Ordering Using Hypergraph Partitioning
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Research and Application of Equipment Fault Diagnosis Based on Cloud Computing
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 706-708Research and Application of Equipment Fault...

Research and Application of Equipment Fault Diagnosis Based on Cloud Computing

Abstract:

Research on remote fault diagnosis of wind power has great significance of protecting grid security and secure operation of wind farm This paper presents the remote fault diagnosis system of wind power based on cloud computing and thoroughly analyzes construction demands and functional structure. Experimental results show that this system can effectively analyze mass monitored data and accurately assess equipment failure. This provides a new idea for cloud computing applied to wind farm fault diagnosis.

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Periodical:

Advanced Materials Research (Volumes 706-708)

Pages:

1898-1901

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.706-708.1898

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Cite this paper

Online since:

June 2013

Authors:

Guang Lei Li, Shu Min Sun, Qing Bo Mao

Keywords:

Cloud Computing, Data Processing, Data Storage, Fault Diagnosis, Wind Farm

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