An experimental modal analysis (EMA) of the wind turbine blade structure reveals the as-built dynamic behavior, specifically the identification of eigenfrequencies, mode shapes, and damping ratios. Traditionally, an EMA of a full-blade structure is conducted under laboratory conditions as part of a certification test campaign for a blade type [1]. A multi-camera stereo vision system effectively detected the first five operating mode shapes compared to traditional wired acceleration sensors [2]. Laser scanners in 2D mode have been used on bridges and wind turbine towers to determine their eigenfrequencies [3].To the authors’ knowledge, this research aims, for the first time, to identify the eigenfrequencies and mode shapes of a blade mounted on a wind turbine in the field using acceleration sensors, cameras, and a laser scanner. For the field measurements, blade A of type LM88.4 P of the Adwen AD 8-180 wind turbine prototype in Bremerhaven, Germany was chosen. The blade was positioned at 6 o'clock with a pitch angle of 86 degrees while the rotor was locked. To conduct an eigenfrequency analysis and an experimental modal analysis (EMA), three independent measurement setups were used: wired acceleration sensors in combination with hammer excitation, and cameras and a laser scanner in combination with hand excitation (HE) and photogrammetric markers. Photogrammetric markers with diameters of 25 cm and 75 cm were randomly placed on the rotor blade (Fig. 1a). Four cameras on the ground recorded images of the markers simultaneously with a drone capturing images from different positions. The drone's data created a virtual test field, and its Real Time Kinematic-based position information was used in a bundle adjustment to calculate the positions of the ground cameras. Additionally, a 2D laser scanner was employed to measure the rotor blade's longitudinal axis without contact (Fig. 1a). For each measurement point, the scanner provided XYZ coordinates along with a timestamp, enabling the continuous tracking of blade deformation over time. To determine the frequencies from the laser scanning data, the rotor blade was divided into 1-meter sections, based approximately on the distance from the blade root. This segmentation is currently approximate, with planned improvements to enhance accuracy. For each 1-meter section, approximately 10 measurement points are available, from which the blade's frequencies can be derived. The analysis of the photogrammetric data is still pending.A total of 38 acceleration sensors were distributed across 13 span-wise blade stations with 3 sensors per station, i.e., two at the leading edge (Fig. 1c) and one at the trailing edge (Fig. 1d). Metal plates were glued directly to the rotor blade surface. Magnets held acceleration sensors. For analysis a commercial software (m+p analyzer) was used. An averaged time signal (out of three strikes) and an H1 estimator were used to generate frequency response functions (FRFs). These FRFs were automatically mapped to their corresponding node, i.e., Degree of Freedom (DoF). A geometrical model of the blade was derived from these nodes. A frequency range of 0Hz-20Hz was selected for this evaluation. Within the software, poles were suggested but selected eventually by the user. Then, synthesized FRFs were generated using a built-in algorithm. From these synthesized FRFs modal parameters, such as eigenfrequency and damping can be extracted. In addition, when linked to the geometrical model, mode shapes can also be derived and visualized from these synthesized FRFs. To evaluate the quality of the determined modal parameters, different criteria can be used, such as a least squares and correlation approach to compare measured data against its synthesized counterpart or a modal assurance criterion (MAC) to assess the quality of determined modes. Succesfully conducted EMA in field, wind excitation partly challenging for post-processing.*Flat/edge dominated mode shapes were well captured; however, torsion shape not captured.*More torsional coupling in higher as-built edge modes than predicted by model, which could be explained with center of mass deviation in flat-wise direction in outboard cross-sections.*Eigenfrequencies determined by laser scanner show same trend as EMA.*Overall tendency of an underestimation (down to -15%) of measured EMA over flat/edge model eigenfrequencies, which could indicate a lower as-built stiffness or a higher as-built mass than predicted by the model.Next: Adapt structural properties of blade model to match eigenfrequencies and modes shapes. x Select Certificate OK Cancel Signer.Digital x Signer.Digital - Confirm Key Listing / Usage Current Domainis trying to detect smartcards connected, or read certificate or use key for signing/encryption. Please select your option. Deny Always Allow Licensed Sites Website License Status Features Action