An experimental study on the data-driven structural health monitoring of large wind turbine blades using a single accelerometer and actuator

The study aimed to investigate the performance of a Structural Health Monitoring (SHM) methodology based on use of a single accelerometer and single actuator in the detection and monitoring of the growth of the damage in the trailing edge of a wind turbine blade. The study used a data-driven vibration SHM, which is considered as a simple, nonparametric method for data compression and information extraction. The methodology found combinations of variables that describe major trends and fluctuations within the vibration response measured on the structure to create a reference state to which new observations were evaluated for damage diagnosis. The blade was artificially excited with an electromechanical actuator that introduced a mechanical impulse in the blade. The vibration responses were measured by accelerometers distributed along the trailing and leading edge of the wind turbine blade. The rationale behind this study was to investigate the combination of accelerometer/actuator location for damage detection sensitivity and damage progression when a single accelerometer and single actuator was used. The experimental study was conducted on an SSP 34 m wind turbine blade with and without introduced damage. Different damage sizes were also considered to evaluate the detectability of the damage. This study complements previous analyses in the same blade where studies on the effect of damage in modal parameters and a multiple sensor SHM technique were evaluated. The results demonstrated that the methodology was able to detect different damage sizes by using only one accelerometer. It was also demonstrated that damage detection and damage progression is affected by the accelerometer/actuator position but this effect is used to provide a rough information about damage location

Damage assessment for wind turbine blades based on a multivariate statistical approach

This paper presents a vibration based structural health monitoring methodology for damage assessment on wind turbine blades made of composite laminates. Normally, wind turbine blades are manufactured by two half shells made by composite laminates which are glued together. This connection must be carefully controlled due to its high probability to disbond which might result in collapse of the whole structure. The delamination between both parts must be monitored not only for detection but also for localisation and severity determination. This investigation consists in a real time monitoring methodology which is based on singular spectrum analysis (SSA) for damage and delamination detection. SSA is able to decompose the vibratory response in a certain number of components based on their covariance distribution. These components, known as Principal Components (PCs), contain information about of the oscillatory patterns of the vibratory response. The PCs are used to create a new space where the data can be projected for better visualization and interpretation. The method suggested is applied herein for a wind turbine blade where the free-vibration responses were recorded and processed by the methodology. Damage for different scenarios viz diferent sizes and locations was introduced on the blade. The results demonstrate a clear damage detection and localization for all damage scenarios and for the different sizes