Abstract
This paper describes and proposes some indicators for continuous monitoring of anomalous
conditions in the hydraulic system of a Kaplan turbine using SCADA data. The indicators are based
on significant deviations between the estimated values for key variables describing the current working
conditions of the components at the plant, and those actually observed. This monitoring strategy requires
models describing the expected values for variables through the whole range of possible working conditions
of the monitored components. These models are normal behavior models able to characterize the
typical relationships between a set of variables used as inputs to the models and the corresponding output
of a target variable whose expected value has to be predicted. The criteria to select the variables to use
in the models are based on the physical working principles of the component. The paper is focused on
models of normal behavior applied to a real case of condition monitoring of a Kaplan turbine regulating
mechanism.
conditions in the hydraulic system of a Kaplan turbine using SCADA data. The indicators are based
on significant deviations between the estimated values for key variables describing the current working
conditions of the components at the plant, and those actually observed. This monitoring strategy requires
models describing the expected values for variables through the whole range of possible working conditions
of the monitored components. These models are normal behavior models able to characterize the
typical relationships between a set of variables used as inputs to the models and the corresponding output
of a target variable whose expected value has to be predicted. The criteria to select the variables to use
in the models are based on the physical working principles of the component. The paper is focused on
models of normal behavior applied to a real case of condition monitoring of a Kaplan turbine regulating
mechanism.
