Abstract

Among the current challenges faced by the wind energy sector, the increase in turbine capacity (including repowering) and the development of new technologies to optimize installation, operation, and maintenance are key factors in progressively reducing costs. In this context, the implementation of advanced sensor systems for Process Health Monitoring (PHM) and Structural Health Monitoring (SHM), as well as the use of predictive models for potential failure detection, is crucial to developing more efficient maintenance strategies. These strategies aim to prevent damage, reduce downtime, and extend the service life of critical components, thereby lowering operation and maintenance (O&M) costs and optimizing asset performance. The present study is part of the 2022 SENECA Public-Private Partnership Project, which aims to improve the O&M of wind energy structures by generating and leveraging data obtained through a novel monitoring system. This system is based on the combination of Fiber Bragg Grating (FBG) optical fiber sensors and piezoresistive fibers based on Carbon Nanotubes (CNTs), which have been coated via an automated extrusion process using thermoplastic matrix materials. This process results in a new single-wire sensor (SWS) technology, designed to be embedded within the structure of wind turbine blades to monitor their structural behavior. Additionally, the sensors enable the collection of data during the manufacturing process. The objective of this work is to enhance knowledge regarding the design, manufacturing, and operation of advanced wind structures by generating data throughout their life cycle. This is achieved through the integration of two types of minimally invasive, single-wire advanced sensors into dry carbon fibers during the resin infusion manufacturing process.