Blade Fault Recognition Based on Signal Processing and Adaptive Fluid Dynamic Modeling

Abstract

An approach for identification of faults in blades of a gas turbine, based on physical modelling, is presented. A measured quantity is used as an input, and the deformed blading configuration is produced as an output. This is achieved without using any kind of “signature,” as is customary in diagnostic procedures for this kind of faults. A fluid dynamic model is used in a manner similar to what is known as “inverse design methods”: the solid boundaries that produce a certain flow field are calculated by prescribing this flow field. In the present case, a signal, corresponding to the pressure variation on the blade-to-blade plane, is measured. The blade cascade geometry that has produced this signal is then produced by the method. In the paper, the method is described, and applications to test cases are presented. The test cases include theoretically produced faults as well as experimental cases where actual measurement data are shown to produce the geometrical deformations that existed in the test engine.