Radar-based sensing of wind turbines blades based on 35 GHz FMCW sensors installed at operational wind turbine towers

The dataset contains radar-based measurements of rotor blades from three operational wind turbines as part of a structural health monitoring system. For this purpose, a sensor box with a 35 GHz radar sensor (about 1 000 measurements per second) and a camera system (about 100 images per second), is mounted on each wind turbine tower at approximately 100 m height. In order to distinguish individual rotor blades, a machine-readable marker printed on a self-adhesive film was applied on the blade’s surface. When a rotor blade passes the sensor, the camera captures an image of the marker while the radar records a measurement. The marker is then identified and the recorded data is assigned to a particular rotor blade. The measurements demonstrate that the damage detection methodology can be transferred to an image processing problem. The challenge is to manage the strong influence from variable environmental and operational conditions, e.g. wind speed, azimuth orientation, that modify the rotor blade appearance in the radargram significantly. The dataset contains measurements from the intact turbine blade conditions, because it was not possible to introduce structural damage.The authors gratefully acknowledge the financial support of this research by the Federal Ministry for Economic Affairs and Climate Action (grant number: 03EE2035A)

Range–doppler analysis for rain detection at Ka-band: numerical and experimental results From laboratory and field measurements

Radar technology in the millimeter-wave frequency band offers many interesting features for wind park surveillance, such as structural monitoring of rotor blades or the detection of bats and birds in the vicinity of wind turbines (WTs). Currently, the majority of WTs are affected by shutdown algorithms to minimize animal fatalities via direct collision with the rotor blades or barotrauma effects. The presence of rain is an important parameter in the definition of those algorithms together with wind speed, temperature, time of the day, and season of the year. A Ka-band frequency-modulated continuous-wave radar (33.4-36.0 GHz) installed at the tower of a 2-MW WT was used during a field study. We have observed characteristic rain-induced patterns, based on the range-Doppler algorithm. To better understand those signatures, we have developed a laboratory experiment and implemented a numerical modeling framework. Experimental and numerical results for rain detection and classification are presented and discussed here. Based on this article, a bat- and bird-friendly adaptive WT control can be developed for improved WT efficiency in periods of rain and, at the same time, reduced animal mortality

Radar-based structural health monitoring of wind turbine blades: The case of damage detection

Structural health monitoring of wind turbine blades is challenging due to its large dimensions, as well as the complex and heterogeneous material system. In this article, we will introduce a radically new structural health monitoring approach that uses permanently installed radar sensors in the microwave and millimetre-wave frequency range for remote and in-service inspection of wind turbine blades. The radar sensor is placed at the tower of the wind turbine and irradiates the electromagnetic waves in the direction of the rotating blades. Experimental results for damage detection of complex structures will be presented in a laboratory environment for the case of a 10-mm-thick glass-fibre-reinforced plastic plate, as well as a real blade-tip sample. </jats:p

Radar imaging system for in-service wind turbine blades inspections : initial results from a field installation at a 2 mw wind turbine

This paper presents an imaging radar system for structural health monitoring (SHM) of wind turbine blades. The imaging radar system developed here is based on two frequency modulated continuous wave (FMCW) radar sensors with a high output power of 30 dBm. They have been developed for the frequency bands of 24,05 GHz-24,25 GHz and 33.4 GHz-36.0 GHz, respectively. Following the successful proof of damage detection and localization in laboratory conditions, we present here the installation of the sensor system at the tower of a 2 MW wind energy plant at 95 m above ground. The realization of the SHM-system will be introduced including the sensor system, the data acquisition framework and the signal processing procedures. We have achieved an imaging of the rotor blades using inverse synthetic aperture radar techniques under changing environmental and operational condition. On top of that, it was demonstrated that the front wall and back wall radar echo can be extracted from the measured signals demonstrating the full penetration of wind turbine blades during operation

Structural Health Monitoring of Aerial Vehicles Using Guided Electromagnetic Waves in K-Band: Initial Damage Detection Results from Drone Flight Testing

This paper introduces a novel structural health monitoring (SHM) approach based on guided electromagnetic waves propagating in a dielectric waveguide in the frequency range from 23.5 to 26 GHz. This approach enables the detection of structural damage based on the analysis of radar signals. This paper presents the performance of the methodology through an experimental case study considering an autonomous heavy lift drone where the whole SHM system is integrated onboard. The whole data acquisition pipeline is described, and damage detection results based on a damage indicator approach are presented and discussed. Finally, this work proves the ability of guided electromagnetic wave technology to be used in flying aerial vehicles. The methodology can be applied to other aircraft structures and application cases in the future