Fiber-optic interferometric acoustic sensors for wind tunnel applications

1993 ◽  
Author(s):  
Young C. Cho
Keyword(s):  
Wind Tunnel ◽  
Fiber Optic ◽  
Acoustic Sensors

scholarly journals Sensing, Actuation, and Control of the SmartX Prototype Morphing Wing in the Wind Tunnel

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 107
Author(s):  
Nakash Nazeer ◽  
Xuerui Wang ◽  
Roger M. Groves
Keyword(s):  
Wind Tunnel ◽  
Optical Fibers ◽  
Fiber Optic ◽  
Experimental Testing ◽  
Single Mode ◽  
Fiber Optic Sensor ◽  
Sensor Data ◽  
Random Errors ◽  
Morphing Wing ◽  
Actuator Dynamics

This paper presents a study on trailing edge deflection estimation for the SmartX camber morphing wing demonstrator. This demonstrator integrates the technologies of smart sensing, smart actuation and smart controls using a six module distributed morphing concept. The morphing sequence is brought about by two actuators present at both ends of each of the morphing modules. The deflection estimation is carried out by interrogating optical fibers that are bonded on to the wing’s inner surface. A novel application is demonstrated using this method that utilizes the least amount of sensors for load monitoring purposes. The fiber optic sensor data is used to measure the deflections of the modules in the wind tunnel using a multi-modal fiber optic sensing approach and is compared to the deflections estimated by the actuators. Each module is probed by single-mode optical fibers that contain just four grating sensors and consider both bending and torsional deformations. The fiber optic method in this work combines the principles of hybrid interferometry and FBG spectral sensing. The analysis involves an initial calibration procedure outside the wind tunnel followed by experimental testing in the wind tunnel. This method is shown to experimentally achieve an accuracy of 2.8 mm deflection with an error of 9%. The error sources, including actuator dynamics, random errors, and nonlinear mechanical backlash, are identified and discussed.

Phase-modulated fiber optic acoustic sensors

1989 ◽  
Vol 28 (2) ◽  
pp. 1-6 ◽  
Author(s):  
N. Lagakos ◽  
J. Bucaro
Keyword(s):  
Fiber Optic ◽  
Acoustic Sensors

Fiber optic acoustic sensors for crack growth diagnostics

2008 ◽  
Author(s):  
Dae-Cheol Seo ◽  
Il-Bum Kwon ◽  
Chi-Yeop Kim ◽  
Dong-Jin Yoon
Keyword(s):  
Crack Growth ◽  
Fiber Optic ◽  
Acoustic Sensors

Use of 2D In2Se3 Single Crystal as a Diaphragm Material for Fabry-Perot Fiber Optic Acoustic Sensors

2019 ◽  
Vol 14 (4) ◽  
pp. 464-469 ◽  
Author(s):  
Sekip-Esat Hayber ◽  
Timucin-Emre Tabaru ◽  
Umut Aydemir ◽  
Omer-Galip Saracoglu
Keyword(s):  
Single Crystal ◽  
Fiber Optic ◽  
Acoustic Sensors ◽  
Fabry Perot

Thin-silica-diaphragm-based fiber optic acoustic sensors

1999 ◽  
Author(s):  
Hai Xiao ◽  
Paul G. Duncan ◽  
Jiangdong Deng ◽  
Wei Huo ◽  
Zhiguang Wang ◽  
...  
Keyword(s):  
Fiber Optic ◽  
Acoustic Sensors

Fiber-optic distributed acoustic sensors (DAS) and applications in railway perimeter security

2018 ◽  
Author(s):  
Xinyu Fan ◽  
Zuyuan He ◽  
Qingwen Liu ◽  
Dian Chen ◽  
Shuai Wang ◽  
...  
Keyword(s):  
Fiber Optic ◽  
Acoustic Sensors

Repeat well logging using earthquake wave amplitudes measured by distributed acoustic sensors

2020 ◽  
Vol 39 (7) ◽  
pp. 513-517
Author(s):  
Roman Pevzner ◽  
Boris Gurevich ◽  
Anastasia Pirogova ◽  
Konstantin Tertyshnikov ◽  
Stanislav Glubokovskikh
Keyword(s):  
Seismic Waves ◽  
Fiber Optic ◽  
Synthetic Data ◽  
Seismic Source ◽  
Small Scale ◽  
Acoustic Sensors ◽  
Linear Strain ◽  
Subsurface Characterization ◽  
Distributed Acoustic Sensing ◽  
Subsurface Monitoring

Well-based technologies for seismic subsurface monitoring increasingly utilize fiber-optic cables installed in boreholes as distributed acoustic sensing (DAS) systems. A DAS cable allows measuring linear strain of the fiber and can serve as an array of densely spaced seismic receivers. The strain amplitudes recorded by the DAS cable depend on the near-well formation properties (the softer the medium, the larger the strain). Thus, these properties can be estimated by measuring relative variations of the amplitudes of seismic waves propagating along the well. An advantage of such an approach to subsurface characterization and monitoring is that no active seismic source is required. Passive sources such as earthquakes can be utilized. A synthetic data example demonstrates viability of the approach for monitoring of small-scale CO2 injection into an aquifer. Two field DAS data examples based on signal recordings from several distant earthquakes show that the relevant properties of the near-well formation can be estimated with an accuracy of approximately 5%.

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