Rotor blade operational data analysis methods and applications for health monitoring of wind turbines using integrated blade sensing

Noah J Myrent, Purdue University

Abstract

Wind energy is one of the fastest growing sources of power production in the world today. In order to extract the maximum potential amount of energy from the wind, a wind turbine's reliability must be a top priority. As utility scale wind turbines increase in size and initial capital investment cost, there also comes an increasing need to monitor the health of the turbine. Currently, most wind turbines do not incorporate blade mounted inertial sensing in addition to blade strain measurements. This approach has the potential to detect inevitable blade damage types early on so that a maintenance schedule can be optimized and the damage does not propagate to the point of blade failure or even damage to the drivetrain components. In this thesis, the wind turbine blade's structural dynamic response is simulated and analyzed with the goal of characterizing the presence and severity of a shear web disbond. Computer models of a five megawatt (MW) offshore utility scale wind turbine were created to develop effective algorithms for detecting such damage. It was shown through data analysis that with the use of blade measurements, a shear web disbond could be quantified according to its length. An aerodynamic sensitivity study was conducted to ensure robustness of the developed detection algorithms. In all analyses, the measurements of the blade's flap-wise acceleration and root pitch- ing moment were the clearest indicators of the presence and severity of a shear web disbond. In fact, the RMS flap-wise blade tip acceleration decreased as much as 35% in the presence of a shear web disbond. These results were correlated to extracted stiffness properties of the damaged blades showing that the torsional and flap-wise stiffnesses were most sensitive to the disbond. Based on the results of the sensitiv- ity study, the damage detection strategy was refined in order to encompass several different wind loading conditions. In addition, a maintenance action strategy was included. A combination of blade and non-blade measurements were formulated into a final algorithm for the detection and quantification of the disbond.

Degree

M.S.M.E.

Advisors

Fleeter, Purdue University.

Subject Area

Mechanical engineering

COinS