The project aimed to overcome the limited number of vibration sensors that can be installed on wind‑energy turbines (WETs) by developing a distance‑based measurement system based on laser‑Doppler vibrometry (LDV). The system was designed to be independent of the turbine platform and capable of measuring vibrations from any point on the outer surface, including moving rotor blades, while the turbine operates in routine conditions. By combining LDV with an image‑based tracking algorithm, the demonstrator could follow the rotating blade and acquire vibration data without physical contact.
The technical work was organised into eight work packages. In the first phase (AP 2 and AP 3) a new LDV hardware platform was built and integrated into a complete sensor system. The hardware build included a high‑resolution LDV head, a mounting rig for onshore wind‑park deployment, and a dedicated control unit. The software package provided hardware control, real‑time data acquisition, a tracking routine that follows the blade tip, and a user interface for monitoring and data logging. Signal processing routines were implemented to filter noise, extract vibration spectra, and perform real‑time analysis. The system was validated in a series of field campaigns that collected a broad data base from different turbine models and operating conditions.
In the second phase (AP 4 and AP 5) extensive measurement campaigns were carried out. The demonstrator was deployed in an onshore wind‑park near Offenbach a.d. Q, where routine measurements were taken on several turbines. Additional campaigns were conducted on research turbines: the AD 8 turbine in Bremerhaven and the Q82 turbine in Pfinztal. These reference measurements provided high‑quality vibration spectra that could be compared with the LDV data. The data set included time‑series of vibration amplitudes, frequency spectra, and blade‑position information, enabling a comprehensive assessment of the measurement method.
Signal evaluation (AP 6) involved filtering, spectral analysis, and real‑time processing of the LDV data. The data analysis (AP 7) focused on interpreting the LDV spectra, comparing them with reference measurements, and evaluating the usefulness, applicability, and limitations of the method for monitoring turbine health. The results showed that the LDV system could reliably capture blade‑vibration signatures, detect resonant modes, and identify potential degradation indicators. The study also identified practical constraints such as the need for accurate blade tracking, environmental noise mitigation, and the influence of wind speed on measurement quality.
The project was coordinated by Fraunhofer IOSB, with significant contributions from Nawrocki Alpin GmbH, which brought two decades of turbine inspection and maintenance experience. Fraunhofer Institute for Wind Energy Systems (IWES) in Bremerhaven and Fraunhofer Institute for Computer Technology (ICT) in Pfinztal provided access to research turbines and reference data. The project ran from 1 December 2019 (formal start) to 31 December 2023, with actual work beginning in January 2020. Seven project meetings were held, most conducted online due to the COVID‑19 pandemic, and a demonstration of the final system took place in January 2022. The collaboration produced a validated LDV demonstrator, a comprehensive vibration data base, and a set of analytical tools that demonstrate the feasibility of non‑contact, distance‑based vibration monitoring for onshore wind farms.