A Structural Health Monitoring Approach for Damage Detection in Wind Turbine Blades Based on Compressed Sensing Acquisition of Acoustic Emission Events

摘要

The wind power capacity installed over the U.S. is growing at a fierce pace.According to American Wind Energy Association reports, between 2007 and 2010,wind power provided more than 35% of all new U.S. electric capacity. Despite therapid growth in wind energy, there are still significant wind energy resources that areunderutilized. The U.S. Department of Energy estimates that offshore wind alonecould offer over 4,000 GW of electrical energy which is four times the nation’s currenttotal generation capacity. In order to harness this renewable resource significantlogistic challenges must be overcome to keep these systems working in harsh offshoreenvironments. The deployment of a structural health monitoring (SHM)systems will be important for these off-shore wind power plants, which are gaining anincreasing interest by investors. Wind turbines come in a number of typologies (e.g.horizontal-axis wind turbine and vertical-axis) and are selected according to thespecific environment in which they are designed to operate. Furthermore, windturbines are complex cyber-physical systems consisting of blades, generators,hydraulics and electronics/computation each of which features different failuremechanisms with unique impact in term of down-time and repair cost. All thesesystems must be continuously monitored in order to ensure they are operating to theirmaximum potential. Unfortunately continuous monitoring using conventional analogto-digital converters will result in a large amount of data that will need to be storedand processed. In this work we study the suitability of compressed sensing (CS) forlong-term acoustic emission (AE)-based SHM of wind turbine blades. In particularthe current work simulates the CS acquisition process as applied to AE data acquiredduring experimental fatigue-to-failure tests (see Figure 1) performed on a full-scaleblade of a horizontal axis wind turbine (HAWT). AE represents a promisingtechnique to develop a monitoring strategy for detecting and possibly localizing thepresence of damage (i.e. delamination) in mechanical components. When damageoccurs or propagates in a structure an acoustic wave is generated by the rapid releasein the internal stress of a material. These AE events can be captured at a relative large