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(a) Pressure responses of the sensor at different temperatures; (b) pressure sensitivity curve at different temperatures.
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Pressure sensors have important prospects in wind pressure monitoring of transmission line towers. Optical pressure sensors are more suitable for transmission line towers due to its anti-electromagnetic interference. However, the fiber pressure sensor is not a suitable choice due to expensive and bulky. In this paper, a compact optical Fabry–Pérot...
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Biological component of cells, protein has been effectively studied and investigated using biological sensors. Photonic crystal-based sensor is highly sensitive optical nanostructure it can be manipulated to affect the motion of photon for users' application. In the proposed work microcavity based photonic crystal biosensor has been designed and in...
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... Благодаря простой конструкции, высокой чувствительности и низкой стоимости предлагаемый волоконно-оптический сенсор имеет потенциальное применение в автомобильной навигации, авиации и биомедицинских областях. Сенсоры давления [15] имеют важные перспективы в мониторинге давления ветра на опорах линий электропередачи. В исследования авторов представлен разработанный компактный оптический сенсор давления Фабри-Перо для измерения давления ветра. ...
This paper presents issues related to the development of
a system for monitoring the displacement of the mountain
range leading to the collapse of the sides of the quarry.
The control system uses chiseled fiber-optic sensors. Fiberoptic sensors are based on Single Mode optical fibers. A
laboratory sample of a point fiber-optic sensor based on a
two-shoulder Mach-Zehnder interferometer using a Single
Mode optical fiber for displacement control has been
developed. The simulation stand of a laboratory sample of
a fiber-optic sensor showed high measurement accuracy,
linearity and can be used to control the stability of the
sides of the quarry after the design has been improved.
The experimental data obtained are processed using the
Wolfram Alpha computer program. A hardware-software
control complex has also been developed with a wide range
of elements that allows you to adjust sensitivity and has
machine learning elements.
This article covers rigorous overview of diverse transduction principles that have enabled successful development of Micro/Nanoelectromechanical Systems (MEMS/NEMS) devices widely used for sensing and actuation. The review begins by classifying various transduction techniques, understanding cross-domain couplings, and discussing underlying working principles that drive these transducer operations. Both actuation and sensing modes of each transduction method are presented along with deeper discussion on the real issues and/or technological challenges that have been/are currently being addressed. The article presents pros and cons of different transduction techniques, presents comparative performance of one over another (in terms of transduction efficiency, force & displacement, nonlinearity, energy requirements, reliability, etc.), and provides scientific insights.
It is essential to detect pressure from a robot’s fingertip in every direction to ensure efficient and secure grasping of objects with diverse shapes. Nevertheless, creating a simple-designed sensor that offers cost-effective and omnidirectional pressure sensing poses substantial difficulties. This is because it often requires more intricate mechanical solutions than when designing non-omnidirectional pressure sensors of robot fingertips. This paper introduces an innovative pressure sensor for fingertips. It utilizes a uniquely designed dynamic focusing cone to visually detect pressure with omnidirectional sensitivity. This approach enables cost-effective measurement of pressure from all sides of the fingertip. The experimental findings demonstrate the great potential of the newly introduced sensor. Its implementation is both straightforward and uncomplicated, offering high sensitivity (0.07 mm/N) in all directions and a broad pressure sensing range (up to 40 N) for robot fingertips.
The nanoplasmonic sensor of the nanograting array has a remarkable ability in label-free and rapid biological detection. The integration of the nanograting array with the standard vertical-cavity surface-emitting lasers (VCSEL) platform can achieve a compact and powerful solution to provide on-chip light sources for biosensing applications. Here, a high sensitivity and label-free integrated VCSELs sensor was developed as a suitable analysis technique for COVID-19 specific receptor binding domain (RBD) protein. The gold nanograting array is integrated on VCSELs to realize the integrated microfluidic plasmonic biosensor of on-chip biosensing. The 850 nm VCSELs are used as a light source to excite the localized surface plasmon resonance (LSPR) effect of the gold nanograting array to detect the concentration of attachments. The refractive index sensitivity of the sensor is 2.99 × 10⁶ nW/RIU. The aptamer of RBD was modified on the surface of the gold nanograting to detect the RBD protein successfully. The biosensor has high sensitivity and a wide detection range of 0.50 ng/mL – 50 µg/mL. This VCSELs biosensor provides an integrated, portable, and miniaturized idea for biomarker detection.
The micro-electromechanical system (MEMS) sensors are suitable devices for vibrational analysis in complex systems. The Fabry–Pérot interferometer (FPI) is used due to its high sensitivity and immunity to electromagnetic interference (EMI). Here, we present the design, fabrication, and characterization of a silicon-on-insulator (SOI) MEMS device, which is embedded in a metallic package and connected to an optical fiber. This integrated micro-opto-electro-mechanical system (MOEMS) sensor contains a mass structure and handle layers coupled with four designed springs built on the device layer. An optical reading system using an FPI is used for displacement interrogation with a demodulation technique implemented in LabVIEW®. The results indicate that our designed MOEMS sensor exhibits a main resonant frequency of 1274 Hz with damping ratio of 0.0173 under running conditions up to 7 g, in agreement with the analytical model. Our experimental findings show that our designed and fabricated MOEMS sensor has the potential for engineering application to monitor vibrations under high-electromagnetic environmental conditions.
In this study, an artificial neural network (ANN) based model is developed for MEMS diaphragm analysis, which does not require difficult and time-consuming FEM processes. ANN-based estimator is generated for static pressure response (d) and dynamic pressure response (f) analysis of TLC (three leaf clover) diaphragms for Fabry-Perot interferometers as an example. TLC is one of the unsealed MEMS design diaphragms formed by three leaves of equal angles. The diaphragms used to train ANNs are designed with SOLIDWORKS and analyzed with ANSYS. A total of 1680 TLC diaphragms are simulated with eight diaphragm parameters (3 for SiO2 material, 4 for geometry, and 1 for pressure) to create a data pool for ANN’s training, validation, and testing processes. 80% of the data is used for training, 15% for validation, and the remaining for testing. Only four geometric parameters are used as input in the ANN estimator, and the material parameters are added to the model with an analytical multiplier. Thus, network models that estimate d and f values for all kinds of diaphragm materials are proposed, with a material-independently trained ANN structure. The performance of the ANN model is compared with the empirical equation suggested in the literature, and its superiority is demonstrated. In addition, the d and f parameters of TLC diaphragms designed with five different materials (Si, In2Se3, Ag, EPDM, Graphene) are estimated to be very close to the real ones. By using the proposed method, analyses of TLC diaphragms are quickly performed without the need for time-consuming and costly design and analysis programs.
More recently, various techniques have been implemented for the sensors manufacturing purpose, such as fiber Bragg gratings fibers (FBG) that allows variable core refractive index suitable for a large scale of measurements types, fiber optic evanescent waves (FOEW) for water parameters measurement, microstructured and crystal photonic optical fibers, polymers optical fiber (POFs), and so on. In this perspective, the objective of this work is to study the reliability and the origin of the resistance of each fiber-matrix interface of the composite materials PMMA/PEEK, Topas/PEEK, and Topas-Zeonex/PEEK. The genetic simulation is based on the probabilistic approach of Weibull to calculate the damage at the interface by crossing the two damages of the matrix and the fiber respectively. The results show that the PMMA/PEEK composite is the most resistant to the mechanical stresses applied compared to those Topas/PEEK and Topas-Zeonex/PEEK; these results were confirmed by the level of damage to the interface observed for the studied materials. The performed calculations are in good agreement with the analytical results of Cox, where he demonstrated that Young's modulus of fibers have an important influence on the shear strength of the fiber-matrix interface of composite materials. Based on the obtained results, the present study gives the opportunity for the proposed materials (PMMA/PEEK and Zeonex/PEEK) to be as potential candidates for the smart digital applications and telecoms aims.
We report on the deployment of MEMS static bifurcation (DC) sensors for the detection of volatile organic compounds (VOCs): hydrogen sulfide and formaldehyde. We demonstrate a sensor that can detect as low as a few ppm of hydrogen sulfide. We also demonstrate a sensor array that can selectively detect formaldehyde in the presence of benzene, a closely related interferent. Toward that end, we investigate the sensitivity and selectivity of two detector polymers—polyaniline (PANI) and poly (2,5-dimethyl aniline) (P25DMA)—to both gases. A semiautomatic method is developed to functionalize individual sensors and sensor arrays with the detector polymers. We found that the sensor array can selectively sense 1 ppm of formaldehyde in the presence of benzene.
