This paper presents an analysis of data taken from several stall initiation events on a GE LM-2500 gas turbine engine. Specifically, the time series of three separate pressure signals located at compressor stages 3, 6, and 15 were analyzed utilizing various signal processing methods to determine the most reliable indicator of incipient stall for this engine. The spectral analyses performed showed that rotating precursor waves traveling around the annulus at approximately half of the rotor speed were the best indicators. Non-linear chaotic time series analyses were also used to predict stall, but it was not as reliable an indicator. Several algorithms were used and it was determined that stall wave perturbations can be reliably identified about 900 revolutions prior to the stall. This work indicates that a single pressure signal located at stage 3 on an LM-2500 gas turbine is sufficient to provide advance warning of more than 2 seconds prior to the fully developed stall event.
About Array Processing Methods for Image Segmentation
