Health Monitoring and Diagnosis of Equipment Based on Multi-sensor Fusion

Authors

  • Xuemei Yao
  • Shaobo Li
  • Yong Yao
  • Xiaoting Xie

DOI:

https://doi.org/10.3991/ijoe.v14i04.8315

Keywords:

Multi-sensor fusion, Monitoring and diagnosis, Evidence theory, Robustness

Abstract


As the information measured by a single sensor cannot reflect the real situation of mechanical devices completely, a multi-sensor data fusion based on evidence theory is introduced. Evidence theory has the advantage of dealing with uncertain information. However, it produces unreasonable conclusions when the evidence conflicts. An improved fusion method is proposed to solve this problem. Basic probability assignment of evidence is corrected according to evidence and sensor weights, and an optimal fusion algorithm is selected by comparing an introduced threshold and a conflict factor. The effectiveness and practicability of the algorithm are tested by simulating the monitoring and diagnosis of rolling bearings. The result shows that the method has better robustness.

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Published

2018-04-26

How to Cite

Yao, X., Li, S., Yao, Y., & Xie, X. (2018). Health Monitoring and Diagnosis of Equipment Based on Multi-sensor Fusion. International Journal of Online and Biomedical Engineering (iJOE), 14(04), pp. 4–19. https://doi.org/10.3991/ijoe.v14i04.8315

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Section

Papers