Interpolation of periodic hidden signal measured at steady-operating conditions on hydroelectric turbine runners

The lack of experimental information can lead to an inaccurate prediction of hydroelectric turbine runners fatigue damage. Therefore, to recover this information, this research aim is the use of existing data measured by strain gauge to interpolate the unknown or not observed information about runner strain over the complete range of the steady-operating conditions for hydroelectric turbine. At steady-operating conditions, a strain signal, measured on the runner, can be separated into three principal components: static, periodic and stochastic. This paper presents the first step of our research that extracts and interpolates the periodic part at steady-operating states. A case study is used to compare two different kriging interpolation methods: the Spatial Kriging Method (based on 2D semivariogram) and the Spatio-Temporal Kriging Method (based on 3D semivariogram). The interpolation results are compared and validated with the experimental values.