Study on Mechanical Equipment Fault Diagnosis System Based on Cloud Computing

Wang Shen Hao; Xin Min Dong; Jie Han; Wen Ping Lei

doi:10.4028/www.scientific.net/AMM.220-223.2520

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223Study on Mechanical Equipment Fault Diagnosis...

Study on Mechanical Equipment Fault Diagnosis System Based on Cloud Computing

Abstract:

Generally working in severe conditions, mechanical equipments are subjected to progressive deterioration of their state. The mechanical failures account for more than 60% of breakdowns of the system. Therefore, the identification of impending mechanical fault is very important to prevent the system from illness running. It generally requires high performance computer to complete the traditional parallel computing, while the parallel FFT algorithm based on Hadoop MapReduce programming model can be realized in the low-end machines. Combining with Cloud Computing and equipment fault diagnosis technology, it can realize the massive data parallel computing and distributed storage. The result of experiment shows that it would provide a good solution and technical support for mechanical equipment on-line monitoring and real-time fault diagnosis.

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Periodical:

Applied Mechanics and Materials (Volumes 220-223)

Pages:

2520-2523

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.220-223.2520

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Online since:

November 2012

Authors:

Wang Shen Hao, Xin Min Dong, Jie Han, Wen Ping Lei

Keywords:

Cloud Computing, Fault Diagnosis, MapReduce, Parallel FFT (Fast Fourier Transform) Algorithm, State Monitoring

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