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This work aims at radar sensors in the frequency band from 57 to 64 GHz that can be embedded in wind turbine blades during manufacturing, enabling non-destructive quality inspection directly after production and structural health monitoring (SHM) during the complete service life of the blade. In this paper, we show the fundamental damage detection capability of this sensor technology during fatigue testing of typical rotor blade materials. Therefore, a frequency modulated continuous wave (FMCW) radar sensor is used for damage diagnostics, and the results are validated by simultaneous camera recordings. Here, we focus on the failure modes delamination, fiber waviness (ondulation), and inter-fiber failure. For each failure mode, three samples have been designed and experimentally investigated during fatigue testing. A damage index has been proposed based on residual, that is, differential, signals exploiting measurements from pristine structural conditions. This study shows that the proposed innovative radar approach is able to detect continuous structural degradation for all failure modes by means of gradual signal changes.
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.
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.
