Data Fusion Algorithm of Fault Diagnosis Considering Sensor Measurement Uncertainty

This paper presents data fusion algorithm of fault diagnosis considering sensor measurement uncertainty. Random-fuzzy variables (RFV) are used to model testing patterns (TPs) and fault template patterns (FTPs) respectively according to on-line sensor monitoring data and typical historical sensor data reflecting every fault mode. A similarity measure is given to calculate matching degree between a TP and each FTP in fault database such that Basic Probability Assignment (BPA) can be obtained by normalizing matching degree. Several BPAs provided by many sensor sources are fused by Dempster's rule of combination. A diagnosis decision-making can be done according to the fusion results. Finally,

[1]  Alessandro Ferrero,et al.  The construction of random-fuzzy variables from the available relevant metrological information , 2008, IEEE Transactions on Instrumentation and Measurement.

[2]  Simona Salicone,et al.  Measurement Uncertainty: An Approach Via the Mathematical Theory of Evidence , 2006 .

[3]  Xianfeng Fan,et al.  Fault diagnosis of machines based on D-S evidence theory. Part 2: Application of the improved D-S evidence theory in gearbox fault diagnosis , 2006, Pattern Recognit. Lett..

[4]  E. Iso,et al.  Measurement Uncertainty and Probability: Guide to the Expression of Uncertainty in Measurement , 1995 .

[5]  Alessandro Ferrero,et al.  The random-fuzzy variables: a new approach to the expression of uncertainty in measurement , 2004, IEEE Transactions on Instrumentation and Measurement.

[6]  Wang,et al.  An Information Fusion Method of Fault Diagnosis Based on Interval Basic Probability Assignment , 2011 .

[7]  Alessandro Ferrero,et al.  Modeling and Processing Measurement Uncertainty Within the Theory of Evidence: Mathematics of Random–Fuzzy Variables , 2007, IEEE Transactions on Instrumentation and Measurement.

[8]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[9]  Alessandro Ferrero,et al.  A method based on random-fuzzy variables for online estimation of the measurement uncertainty of DSP-based instruments , 2004, IEEE Transactions on Instrumentation and Measurement.

[10]  S. Standard.  GUIDE TO THE EXPRESSION OF UNCERTAINTY IN MEASUREMENT , 2006 .

[11]  A. Ferrero,et al.  The random-fuzzy variables: A new approach for the expression of uncertainty in measurement , 2003, Proceedings of the 20th IEEE Instrumentation Technology Conference (Cat. No.03CH37412).