Acoustic Optical Fiber Sensor Based on Graphene Oxide Membrane

Abstract

A Fabry–Pérot acoustic sensor based on a graphene oxide membrane was developed with the aim to achieve a faster and simpler fabrication procedure when compared to similar graphene-based acoustic sensors. In addition, the proposed sensor was fabricated using methods that reduce chemical hazards and environmental impacts. The developed sensor, with an optical cavity of around 246 µm, showed a constant reflected signal amplitude of 6.8 ± 0.1 dB for 100 nm wavelength range. The sensor attained a wideband operation range between 20 and 100 kHz, with a maximum signal-to-noise ratio (SNR) of 32.7 dB at 25 kHz. The stability and sensitivity to temperatures up to 90 °C was also studied. Moreover, the proposed sensor offers the possibility to be applied as a wideband microphone or to be applied in more complex systems for structural analysis or imaging.

Small-volume highly-sensitive all-optical gas sensor using non-resonant photoacoustic spectroscopy with dual silicon cantilever optical microphones

“…It shows a favorable flat frequency response within 2.5 dB variation between 5 Hz and 250 Hz. To the best of our knowledge, the response sensitivity based on miniaturized FP interferometry in the low frequency range in this work is optimum among previously reported optical acoustic sensors so far [39] , [40] , [41] , [42] , [43] .

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Sound Detection Monitoring Tool in CNC Milling Sounds by K-Means Clustering Algorithm

“…For this reason, the purpose of this simulation is to monitor the milling process while the machine is running by simulating a sound detection [ 6 ] program in the LabVIEW software [ 7 ]. This program uses a microphone [ 8 ] to capture the sound of the milling process and transmit it to the program, where the results of the simulation are made in the form of images and frequency graphs, and amplitude and applying fast Fourier transform (FFT) [ 9 ] for the analysis of spectral measurements will be clustered by a K-means algorithm [ 10 , 11 ]. This author [ 12 ] compares batch K-means processing with K-means streaming processing based on value, cost distance, and cluster distribution factors to analyze the attributes of batch K-means processing and K-means streaming processing and also to find the limitations of both processing models.…”

Study of Intra-Chamber Processes in Solid Rocket Motors by Fiber Optic Sensors

“…Nowadays, many tasks can be solved in science and technics with the help of FOSs. They are useful for measuring deformation [ 9 ], temperature [ 10 , 11 , 12 ], vibration [ 13 ], concentration of substances [ 14 ], rotation speed [ 15 ], refractive index [ 16 ], pressure [ 17 ], liquid level [ 18 ], acceleration [ 19 ], acoustics [ 20 , 21 , 22 ], and other parameters [ 2 , 23 , 24 , 25 ]. Additionally, new types of fiber promise to open new opportunities for such monitoring devices [ 26 , 27 ].…”