Modeling the dynamic behavior of turbine runner blades during transients using indirect measurements

Abstract

Turbine start-up transients are induced by the wicket gates opening sequence and generate high amplitude stress cycles. These stress cycles have a detrimental effect leading to faster crack growth in the runner blades. Using a series of direct measurements taken on a prototype runner in order to find the optimal start-up parameters exposes both the runner and the instrumentation to a series of successive damaging transient events during the optimization process. To solve this, finding sensors strongly correlated to strain gauges and whose signals can be easily obtained to identify a model to predict the strain, instead of directly measuring it, would reduce the risk, cost and downtime associated with a measurement campaign. This paper shows that turbine shaft torsion measurements is highly correlated to the strain at a runner blade hotspot, and we demonstrate that the ARMAX model can be used to represent the dynamic system in order to minimize the strain on blades.