Fault diagnosis for aero-engine multi-redundant smart sensors based on data fusion

Abstract

In order to diagnosis the aero-engine multi-redundant smart sensors, a method based on data fusion was proposed. In this method, an improved fuzzy C-means clustering algorithm was used to get a fusion value based on multisensing units' information, and then the residuals between the fusion value and measured values of the sensing units could be calculated. After that, the residuals could be used to monitor the health conditions of the sensors. The simulation results showed that the fusion value has a high accuracy, and the absolute error is less than 0.5°C, and also online sensing units fault location could be completed in the form of fault vector. © 2014 Springer-Verlag.