This study investigates dynamic displacement estimation using double-time-integrated acceleration signals for future application in load monitoring based on accelerometers. To estimate displacements without amplitude distortion, a tilt error compensation method for low-frequency vibrations of tower structures using the static bending line without the need for additional sensors is presented. The method is validated using a full-scale onshore wind turbine tower and a terrestrial laser scanner.

Wind turbines subject their components to highly variable loads over very long lifetimes. Tests of components like the pitch bearings that connect rotor blades and the rotor hub serve to validate their ability to withstand these loads. Due to the complexity of the operational loads, the definition of test programs is challenging. This work outlines a method that defines wear test programs for specific pitch bearings and gives a case study for an example turbine.

In order to provide early warnings of faults in the main bearing, a fault detection system is developed by applying an anomaly detector based on principal component analysis. Without the need to obtain the fault history or install additional equipment or sensors that would require a larger investment, this model is constructed using only healthy supervisory control and data acquisition (SCADA) data. The results obtained enable failure detection even months before the fatal breakdown takes place.