Research on Equipment Fault Diagnosis Method Based on Multi-Sensor Data Fusion

Bin Ma; Lin Chong Hao; Wan Jiang Zhang; Jing Dai; Zhong Hua Han

doi:10.4028/www.scientific.net/AMR.466-467.1222

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 466-467Research on Equipment Fault Diagnosis Method Based...

Research on Equipment Fault Diagnosis Method Based on Multi-Sensor Data Fusion

Abstract:

In this paper, we presented an equipment fault diagnosis method based on multi-sensor data fusion, in order to solve the problems such as uncertainty, imprecision and low reliability caused by using a single sensor to diagnose the equipment faults. We used a variety of sensors to collect the data for diagnosed objects and fused the data by using D-S evidence theory, according to the change of confidence and uncertainty, diagnosed whether the faults happened. Experimental results show that, the D-S evidence theory algorithm can reduce the uncertainty of the results of fault diagnosis, improved diagnostic accuracy and reliability, and compared with the fault diagnosis using a single sensor, this method has a better effect.

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Periodical:

Advanced Materials Research (Volumes 466-467)

Pages:

1222-1226

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.466-467.1222

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Online since:

February 2012

Authors:

Bin Ma, Lin Chong Hao, Wan Jiang Zhang, Jing Dai, Zhong Hua Han

Keywords:

Data Fusion, D-S Evidence Theory, Fault Diagnosis, Multi-Sensor

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