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MEMS Accelerometers

Authors: --- ---
ISBN: 9783038974147 / 9783038974154 Year: Pages: 252 DOI: 10.3390/books978-3-03897-415-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc.

Keywords

low-temperature co-fired ceramic (LTCC) --- capacitive accelerometer --- wireless --- process optimization --- performance characterization --- MEMS accelerometer --- mismatch of parasitic capacitance --- electrostatic stiffness --- high acceleration sensor --- piezoresistive effect --- MEMS --- micro machining --- turbulent kinetic energy dissipation rate --- probe --- microelectromechanical systems (MEMS) piezoresistive sensor chip --- Taguchi method --- marine environmental monitoring --- accelerometer --- frequency --- acceleration --- heat convection --- motion analysis --- auto-encoder --- dance classification --- deep learning --- self-coaching --- wavelet packet --- classification of horse gaits --- MEMS sensors --- gait analysis --- rehabilitation assessment --- body sensor network --- MEMS accelerometer --- electromechanical delta-sigma --- built-in self-test --- in situ self-testing --- digital resonator --- accelerometer --- activity monitoring --- regularity of activity --- sleep time duration detection --- indoor positioning --- WiFi-RSSI radio map --- MEMS-IMU accelerometer --- zero-velocity update --- step detection --- stride length estimation --- field emission --- hybrid integrated --- vacuum microelectronic --- cathode tips array --- interface ASIC --- micro-electro-mechanical systems (MEMS) --- delaying mechanism --- safety and arming system --- accelerometer --- multi-axis sensing --- capacitive transduction --- inertial sensors --- three-axis accelerometer --- micromachining --- miniaturization --- stereo visual-inertial odometry --- fault tolerant --- hostile environment --- MEMS-IMU --- mode splitting --- Kerr noise --- angular-rate sensing --- whispering-gallery-mode --- optical microresonator --- three-axis acceleration sensor --- MEMS technology --- sensitivity --- L-shaped beam --- n/a

Smart Sensors for Structural Health Monitoring

Authors: --- ---
ISBN: 9783039217588 / 9783039217595 Year: Pages: 342 DOI: 10.3390/books978-3-03921-759-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Abstract

Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).

Keywords

optical crack growth sensor --- digital sampling moiré --- 2D crack growth --- calibration --- concrete crack --- feature extraction --- mapping construction --- fuzzy classification --- rotary ultrasonic array --- bending stiffness --- damage identification --- environmental noise --- bridge --- test vehicle --- structural impact monitoring --- sensors distribution optimization --- NSGA-II --- energy analysis of wavelet band --- principal component analysis --- transmission tower --- settlement --- wind force --- acceleration --- modal frequencies --- sudden event monitoring --- wireless smart sensors --- demand-based nodes --- event-triggered sensing --- data fusion --- patch antenna --- sensor --- structural health monitoring --- crack identification --- resonant frequency --- damage identification --- sensor optimization --- Virtual Distortion Method (VDM) --- Particle Swarm Optimization (PSO) algorithm --- sensitivity --- structural health monitoring --- piezoelectric wafer active sensors --- active sensing --- passive sensing --- damage detection --- acoustic emission --- uniaxial stress measurement --- structural steel members --- amplitude spectrum --- phase spectrum --- shear-wave birefringence --- acoustoelastic effect --- damage detection --- smartphones --- steel frame --- shaking table tests --- wavelet packet decomposition --- low-velocity impacts --- strain wave --- impactor stiffness --- data processing --- feature selection --- impact identification --- crack --- strain --- distributed dense sensor network --- structural health monitoring --- fibre bundle --- reflective optical sensor --- tip clearance --- turbine --- aero engine --- principal component analysis --- space window --- time window --- damage detection --- length effect --- stress detection --- electromagnetic oscillation --- steel strand --- concrete structures --- SHM --- stretching method --- model updating --- displacement sensor --- helical antenna --- resonant frequency --- perturbation theory --- normal mode --- wheel minor defect --- high-speed train --- online wayside detection --- Bayesian blind source separation --- FBG sensor array

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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eng (2)


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2019 (2)