Design and simulation of a multi-function MEMS sensor for health and usage monitoring.

Health and usage monitoring as a technique for online test, diagnosis or prognosis of structures and systems has evolved as a key technology for future critical systems. The technology, often referred to as HUMS is usually based around sensors that must be more reliable than the system or structure they are monitoring. This paper proposes a fault tolerant sensor architecture and demonstrates the feasibility of realising this architecture through the design of a dual mode humidity/pressure MEMS sensor with an integrated temperature function. The sensor has a simple structure, good linearity and sensitivity, and the potential for implementation of built-in-self-test features. We also propose a re-configurable sensor network based on the multi-functional sensor concept that supports both normal operational and fail safe modes. The architecture has the potential to significantly increase system reliability and supports a reduction in the number of sensors required in future HUMS devices. The technique has potential in a wide range of applications, especially within wireless sensor networks

Overview of sensors suitable for active flow control methods

Hlavným cieľom tejto bakalárskej práce bolo vytvorenie prehľadu vyvíjaných a už aplikovaných senzorov pre účely aktívneho riadenia prúdov. Senzory musia splňovať niektoré podmienky, preto výber senzorov bol naviazaný na reálnych výsledkoch testovacích programov, popis ktorých tvorí prvú časť tejto bakalárskej práce. Opis technológie a princíp fungovania senzorov je popísaný v druhej časti tejto práce.The main purpose of this bachelor thesis was to create the overview of the sensors developed for the future active flow control applications and overview the sensors already used in the active flow control applications. The sensors have to fulfil several requirements, so selection for the overview was based on the real flight test programs results, which were described in the first part of the thesis. The sensors technology description and operation principles were included in the second part of the thesis

Iris segmentation

The quality of eye image data become degraded particularly when the image is taken in the non-cooperative acquisition environment such as under visible wavelength illumination. Consequently, this environmental condition may lead to noisy eye images, incorrect localization of limbic and pupillary boundaries and eventually degrade the performance of iris recognition system. Hence, this study has compared several segmentation methods to address the abovementioned issues. The results show that Circular Hough transform method is the best segmentation method with the best overall accuracy, error rate and decidability index that more tolerant to ‘noise’ such as reflection

MEMS-based thermal management of high heat flux devices edifice: Embedded droplet impingement for integrated cooling of electronics

Increases in microprocessor power dissipation coupled with reductions in feature sizes due to manufacturing process improvements have resulted in continuously increasing heat fluxes. The ever increasing chip-level heat flux has necessitated the development of thermal management devices based on spray and evaporative cooling. This lecture presents a comprehensive review of liquid and evaporative cooling research applied to thermal management of electronics. It also outlines the challenges to practical implementation and future research needs. This presentation also describes the development of EDIFICE: Embedded Droplet Impingement For Integrated Cooling of Electronics. The EDIFICE project seeks to develop an integrated droplet impingement cooling device for removing chip heat fluxes over 100 W/cm2, employing latent heat of vaporization of dielectric fluids. Micro-manufacturing and MEMS (Micro Electro-Mechanical Systems) will be discussed as enabling technologies for innovative cooling schemes recently proposed. Micro-spray nozzles are fabricated to produce 50-100 micron droplets coupled with surface texturing on the backside of the chip to promote droplet spreading and evaporation. A novel feature to enable adaptive on-demand cooling is MEMS sensing (on-chip temperature, remote IR temperature and ultrasonic dielectric film thickness) and MEMS actuation. EDIFICE is integrated within the electronics package and fabricated using advanced micro-manufacturing technologies (e.g., Deep Reactive Ion Etching (DRIE) and CMOS CMU-MEMS). The development of EDIFICE involves modeling, CFD simulations, and physical experimentation on test beds. This lecture will then examine jet impingement cooling of EDIFICE with a dielectric coolant and the influence of fluid properties, micro spray characteristics, and surface evaporation. The development of micro nozzles, micro-structured surface texturing, and system integration of the evaporator will also be discussed

A CubeSAT payload for in-situ monitoring of pentacene degradation due to atomic oxygen etching in LEO

This paper reports and discusses the design and ground tests of a CubeSat payload which allows to measure, in-situ and in real time, the degradation of a polymer of electronic interest due to atomic oxygen etching in LEO. It provides real-time information on how the degradation occurs, eliminating the need to work with samples recovered once the mission has finished. The polymer, TIPS-Pentacene, is deposited on the surface of a microelectromechanical (MEMS) cantilever, which works as a resonator embedded in a Pulsed Digital Oscillator circuit. The mass losses in the polymer due to atomic oxygen corrosion produce variations in the resonant frequency of the MEMS, which is continuously sensed by the circuit and transmitted to the ground. This way, polymer mass losses around 10-12 kg can be detected during the mission. The payload is a part of the 3Cat-1 mission, a nano-satellite aimed at carrying out several scientific experiments.Peer ReviewedPostprint (author's final draft

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

The Deformable Mirror Demonstration Mission (DeMi) CubeSat: optomechanical design validation and laboratory calibration

Coronagraphs on future space telescopes will require precise wavefront correction to detect Earth-like exoplanets near their host stars. High-actuator count microelectromechanical system (MEMS) deformable mirrors provide wavefront control with low size, weight, and power. The Deformable Mirror Demonstration Mission (DeMi) payload will demonstrate a 140 actuator MEMS deformable mirror (DM) with \SI{5.5}{\micro\meter} maximum stroke. We present the flight optomechanical design, lab tests of the flight wavefront sensor and wavefront reconstructor, and simulations of closed-loop control of wavefront aberrations. We also present the compact flight DM controller, capable of driving up to 192 actuator channels at 0-250V with 14-bit resolution. Two embedded Raspberry Pi 3 compute modules are used for task management and wavefront reconstruction. The spacecraft is a 6U CubeSat (30 cm x 20 cm x 10 cm) and launch is planned for 2019.Comment: 15 pages, 10 figues. Presented at SPIE Astronomical Telescopes + Instrumentation, Austin, Texas, US

Development of a robust structural health monitoring system for wind turbine foundations

The construction of onshore wind turbines has rapidly been increasing as the UK attempts to meet its renewable energy targets. As the UK’s future energy depends more on wind farms, safety and security are critical to the success of this renewable energy source. Structural integrity is a critical element of this security of supply. With the stochastic nature of the load regime a bespoke low cost structural health monitoring system is required to monitor integrity. This paper presents an assessment of ‘embedded can’ style foundation failure modes in large onshore wind turbines and proposes a novel condition based monitoring solution to aid in early warning of failure

Addressing the Smart Systems Design Challenge: The SMAC Platform

This article presents the concepts, the organization, and the preliminary application results of SMAC, a smart systems co-design platform. The SMAC platform, which has been developed as Integrated Project (IP) of the 7th ICT Call under the Objective 3.2 \u201cSmart components and Smart Systems integration\u201d addresses the challenges of the integration of heterogeneous and conflicting domains that emerge in the design of smart systems. SMAC includes methodologies and EDA tools enabling multi-disciplinary and multi-scale modelling and design, simulation of multidomain systems, subsystems and components at different levels of abstraction, system integration and exploration for optimization of functional and non-functional metrics. The article presents the preliminary results obtained by adopting the SMAC platform for the design of a limb tracking smart system

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT