Equipment Condition Monitoring and Diagnosis System Based on Evidence Weight

Xuemei Yao, Shaobo Li, Ansi Zhang


To ensure the safety and reliability of equipment and effectively prevent the occurrence of major accidents, a monitoring and diagnosis system of equipment condition is proposed in this paper. First, a perceptual model of four layers, which can collect the original data of equipment by sensors and analyze the real-time information with intelligent algorithms and display the decision making on the screen, is designed. Second, a method of condition monitoring and diagnosis based on evidence weight is proposed. The basic probability assignment of evidence is corrected by Mahalanobis distance and sensor weight. A threshold is introduced to select the appropriate fusion rule by comparing the relationship between threshold and conflict factor. In order to verify the effectiveness and practicability of the method, the improved fusion algorithm is applied to the monitoring and diagnosis of centrifugal pumps. Finally, a prototype system is implemented to illustrate the validity of the system in practice.


data fusion; monitoring;evidence theory; intelligent diagnosis

Full Text:


International Journal of Online Engineering (iJOE).ISSN: 1861-2121
Creative Commons License
Web of Science ESCI logo Engineering Information logo INSPEC logo DBLP logo ELSEVIER Scopus logo EBSCO logo Ulrich's logoGoogle Scholar logo Microsoft® Academic Search