This work presents a distributed optical fiber specklegram sensor (FSS) specifically designed for the detection and localization of water leaks. The sensor analyzes specklegram images generated by a No-Core Fiber (NCF) under different water leak conditions, employing a low-cost CCD camera as an interrogation unit. To enhance the accuracy of leak detection, a convolutional neural network (CNN) model is employed to post-process the specklegram images for monitoring the different water leak conditions. The sensor demonstrates high sensitivity, accurately detecting water volumes as small as 0.1 mL. In the initial series of experiments, the sensor achieved a remarkable 100% accuracy in predicting the location of leak spots situated 1 cm apart. However, in subsequent rounds of the experiment, a slight reduction in accuracy was observed (87.5%) due to the issue of water droplet overflow across the Kapton tape used to mark the various test leak spots after multiple cycles of water addition and removal. Therefore, employing an impermeable material for the demarcation will mitigate the water droplet overflow problem. In summary, the proposed sensor offers an efficient approach for water leak detection through the application of machine learning-based specklegram analysis. The findings of this research underscore the potential of FSS as a low-cost, easily implementable, and real-time monitoring system for the detection and localization of water leaks.
This study presents an assembly-free ball lens structure at the tip of tapered multimode optical fiber to enhance the light collection efficiency for pH measurements. A 35 µm diameter ball lens was fabricated at the sensor tip. In addition, a thin layer of fluorescence dye was mixed with sol-gel that formed at the fiber tip for pH sensing. The simulation result demonstrates the light propagation on the ball lens tip. The experiment results reveal that the proposed sensor has a rapid response time (< 3 seconds), high sensitivity, and pinpoint accuracy (±1.0%) in the pH range of 6.0-8.0.
This paper studies the use of Microsphere Photolithography (MPL) as an alternative to Focused Ion Beam milling or e-beam lithography to pattern plasmonic fiber-optic based sensors. In the MPL approach, silica microspheres are self-assembled to form a Hexagonal Close-Packed (HCP) array on top of a layer of photoresist. The microspheres serve as an optical element and focus collimated UV radiation to an array of photonic jets inside the photoresist layer. The exposed region is dependent on the angle of incidence of the UV radiation which facilitates hierarchical patterning. Pattern transfer can be accomplished using either etching or lift-off with the size of the features dependent on the exposure dose. While low-cost and very scalable, the use of MPL influences the design and performance of the fiber probe in several ways. Specifically, the entire cleaved face is patterned without alignment to the fiber core and any defects in the self-assembled microsphere lattice are transferred to the surface. This paper presents the low-cost fabrication of Extraordinary Optical Transmission (EOT) type plasmonic fiber-optic based sensors. The sensors consist of a thin aluminum film on the cleaved face of single mode optical fiber, perforated with a HCP hole-array. At resonance, Extraordinary Optical Transmission (EOT), decreases the reflection from the fiber tip. The conditions for resonance are dependent on the local environment surrounding the fiber tip and the resonant wavelength can be used to measure the index of refraction of a liquid. Experiments show that viable sensors can be created with MPL. The reflection spectra of the sensors was measured in various concentrations of sugar water with a measured sensitivity of 8.33 mg/mL/nm. These results are compared to simulation results which provides a sensitivity analysis of the sensors.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.