Fault Detection for Gas Turbine Sensors Using I/O Dynamic Linear Models: Methodology of Fault Code Generation

Abstract

This paper presents a methodology of sensor diagnosis which appears to be particularly suitable also for application in the field of small/medium power size industrial gas turbines. The methodology is based on the Analytical Redundancy technique and uses ARX (Auto Regressive with eXternal input) MISO (Multi-Input/Single-Output) linear dynamic models obtained from time series data of the gas turbine operating condition. The linear models allow the on-line calculation of some measurable parameter starting from the values of other measured parameters. The comparison between computed and measured values of the same parameters allows setting-up a vector of residuals which, if compared with the columns of the fault matrix, permits the identification of a possible sensor fault. The initial applications of the methodology to a single-shaft industrial gas turbine show an unambiguous and certain detection and isolation of fault in sensors used both in the measurement only and in feedback by the machine control system.