Vibration monitoring of wind-turbine blades through optical fiber sensors

Author(s):  
Marco Belloli ◽  
Gabriele Cazzulani ◽  
Simone Cinquemani ◽  
Stefano Marabelli ◽  
Ilmas Bayati
Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1818
Author(s):  
Mattia Francesco Bado ◽  
Joan R. Casas

The present work is a comprehensive collection of recently published research articles on Structural Health Monitoring (SHM) campaigns performed by means of Distributed Optical Fiber Sensors (DOFS). The latter are cutting-edge strain, temperature and vibration monitoring tools with a large potential pool, namely their minimal intrusiveness, accuracy, ease of deployment and more. Its most state-of-the-art feature, though, is the ability to perform measurements with very small spatial resolutions (as small as 0.63 mm). This review article intends to introduce, inform and advise the readers on various DOFS deployment methodologies for the assessment of the residual ability of a structure to continue serving its intended purpose. By collecting in a single place these recent efforts, advancements and findings, the authors intend to contribute to the goal of collective growth towards an efficient SHM. The current work is structured in a manner that allows for the single consultation of any specific DOFS application field, i.e., laboratory experimentation, the built environment (bridges, buildings, roads, etc.), geotechnical constructions, tunnels, pipelines and wind turbines. Beforehand, a brief section was constructed around the recent progress on the study of the strain transfer mechanisms occurring in the multi-layered sensing system inherent to any DOFS deployment (different kinds of fiber claddings, coatings and bonding adhesives). Finally, a section is also dedicated to ideas and concepts for those novel DOFS applications which may very well represent the future of SHM.


Author(s):  
Paolo Pennacchi ◽  
Gabriele Cazzulani ◽  
Alejandro Silva

Abstract This paper investigates the possibility of identifying and monitoring the modal shapes of a turbine blade by means of continuous optical fiber sensors based on Optical Backscatter Reflectometry (OBR). The advantage of this approach would be the possibility of embedding the sensors in future carbon fiber blades, in order to make this modal analysis approach available also for the blade operating conditions, since no modifications in the blade fluid-structure interaction occur. The paper describes the proposed method and provides some experimental results obtained on a 3D printed model of an existing steam turbine blade.


Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6127
Author(s):  
Catarina S. Monteiro ◽  
António V. Rodrigues ◽  
Duarte Viveiros ◽  
Cassiano Linhares ◽  
Hélder Mendes ◽  
...  

Power transformers are central elements of power transmission systems and their deterioration can lead to system failures, causing major disruptions in service. Catastrophic failures can occur, posing major environmental hazards due to fires, explosions, or oil spillage. Early fault detection can be accomplished or estimated using electrical sensors or a chemical analysis of oil or gas samples. Conventional methods are incapable of real-time measurements with a low electrical noise due to time-consuming analyses or susceptibility to electromagnetic interference. Optical fiber sensors, passive elements that are immune to electromagnetic noise, are capable of structural monitoring by being enclosed in power transformers. In this work, optical fiber sensors embedded in 3D printed structures are studied for vibration monitoring. The fiber sensor is encapsulated between two pressboard spacers, simulating the conditions inside the power transformer, and characterized for vibrations with frequencies between 10 and 800 Hz, with a constant acceleration of 10 m/s2. Thermal aging and electrical tests are also accomplished, aiming to study the oil compatibility of the 3D printed structure. The results reported in this work suggest that structural monitoring in power transformers can be achieved using optical fiber sensors, prospecting real-time monitoring.


2009 ◽  
Vol 129 (5) ◽  
pp. 689-695
Author(s):  
Masayuki Minowa ◽  
Shinichi Sumi ◽  
Masayasu Minami ◽  
Kenji Horii

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