Development of an Ultrasonic NDT System for Automated In-Situ Inspection of Wind Turbine Blades - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Development of an Ultrasonic NDT System for Automated In-Situ Inspection of Wind Turbine Blades

Résumé

It is crucial to maintain wind turbine blades regularly, due to the high stress leading to defects or even damage. Conventional methods require shipping the blades to a workshop for inspection off-site, which is extremely time-consuming and very costly. This work investigates using pulse-echo ultrasound to detect internal damages in wind turbine blades without the necessity to ship the blades off-site. A prototype of 2D ultrasonic non-destructive testing (NDT) system has been developed and optimised for in-situ wind turbine blade inspection. The system is designed to be light weight so it can be easily carried by an inspector climbing onto the wind turbine blade for in-situ inspection. It can be operated in 1D A-Scan, 2D C-Scan or 3D Volume Scan. A software system has been developed to control the automated scanning and show the damage areas in a 2D/3D map with different colours so that the inspector can easily identify the damage areas. Experiments on Glass Fibre Reinforced Plastics (GFRP) and wind turbine blades (made of GFRP) samples showed that internal defects can be detected. The main advantages of this system are fully automated 2D spatial scanning and flaw displaying. It is potentially to be used for in-situ inspection to save maintenance time and hence considered to be economically beneficial for the wind energy industry.
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Dates et versions

hal-01020459 , version 1 (08-07-2014)

Identifiants

  • HAL Id : hal-01020459 , version 1

Citer

Guoliang Ye, Ben Neal, Alex Boot, Vassilios Kappatos, Cem Selcuk, et al.. Development of an Ultrasonic NDT System for Automated In-Situ Inspection of Wind Turbine Blades. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01020459⟩
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