Experimental study on engine gas-path component fault monitoring using exhaust gas electrostatic signal

Abstract

This paper presents the recent development in engine gas-path components health monitoring using electrostatic sensors in combination with signal-processing techniques. Two ground-based engine electrostatic monitoring experiments are reported and the exhaust gas electrostatic monitoring signal-based fault-detection method is proposed. It is found that the water washing, oil leakage and combustor linear cracking result in an increase in the activity level of the electrostatic monitoring signal, which can be detected by the electrostatic monitoring system. For on-line health monitoring of the gas-path components, a baseline model-based fault-detection method is proposed and the multivariate state estimation technique is used to establish the baseline model for the electrostatic monitoring signal. The method is applied to a data set from a turbo-shaft engine electrostatic monitoring experiment. The results of the case study show that the system with the developed method is capable of detecting the gas-path component fault in an on-line fashion.