1,868 research outputs found

    A framework to Calibrate a MEMS Sensor Network

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    International audienceThe Smart Surface project aims at designing an integrated micro-manipulator based on an array of micromodules connected with a 2D array topology network. Each micromodule comprises a sensor, an actuator and a processing unit. One of the aims of the processing unit is to differentiate the shape of the part that is put on top of the Smart Surface. From a set of shapes this differentiation is done through a distributed algorithm that we call a criterion. The article presents Sensor Network Calibrator (SNC), a calibrator which allows to parametrize the Smart Surface and to determine the necessary number of sensors required by our Smart Surface. The tests will show that SNC is of great importance for choosing the number of sensors, and therefore to determine the size of the sensors grid

    FLEXIBLE LOW-COST HW/SW ARCHITECTURES FOR TEST, CALIBRATION AND CONDITIONING OF MEMS SENSOR SYSTEMS

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    During the last years smart sensors based on Micro-Electro-Mechanical systems (MEMS) are widely spreading over various fields as automotive, biomedical, optical and consumer, and nowadays they represent the outstanding state of the art. The reasons of their diffusion is related to the capability to measure physical and chemical information using miniaturized components. The developing of this kind of architectures, due to the heterogeneities of their components, requires a very complex design flow, due to the utilization of both mechanical parts typical of the MEMS sensor and electronic components for the interfacing and the conditioning. In these kind of systems testing activities gain a considerable importance, and they concern various phases of the life-cycle of a MEMS based system. Indeed, since the design phase of the sensor, the validation of the design by the extraction of characteristic parameters is important, because they are necessary to design the sensor interface circuit. Moreover, this kind of architecture requires techniques for the calibration and the evaluation of the whole system in addition to the traditional methods for the testing of the control circuitry. The first part of this research work addresses the testing optimization by the developing of different hardware/software architecture for the different testing stages of the developing flow of a MEMS based system. A flexible and low-cost platform for the characterization and the prototyping of MEMS sensors has been developed in order to provide an environment that allows also to support the design of the sensor interface. To reduce the reengineering time requested during the verification testing a universal client-server architecture has been designed to provide a unique framework to test different kind of devices, using different development environment and programming languages. Because the use of ATE during the engineering phase of the calibration algorithm is expensive in terms of ATE’s occupation time, since it requires the interruption of the production process, a flexible and easily adaptable low-cost hardware/software architecture for the calibration and the evaluation of the performance has been developed in order to allow the developing of the calibration algorithm in a user-friendly environment that permits also to realize a small and medium volume production. The second part of the research work deals with a topic that is becoming ever more important in the field of applications for MEMS sensors, and concerns the capability to combine information extracted from different typologies of sensors (typically accelerometers, gyroscopes and magnetometers) to obtain more complex information. In this context two different algorithm for the sensor fusion has been analyzed and developed: the first one is a fully software algorithm that has been used as a means to estimate how much the errors in MEMS sensor data affect the estimation of the parameter computed using a sensor fusion algorithm; the second one, instead, is a sensor fusion algorithm based on a simplified Kalman filter. Starting from this algorithm, a bit-true model in Mathworks Simulink(TM) has been created as a system study for the implementation of the algorithm on chip

    Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

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    The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

    LGC-Net: A Lightweight Gyroscope Calibration Network for Efficient Attitude Estimation

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    This paper presents a lightweight, efficient calibration neural network model for denoising low-cost microelectromechanical system (MEMS) gyroscope and estimating the attitude of a robot in real-time. The key idea is extracting local and global features from the time window of inertial measurement units (IMU) measurements to regress the output compensation components for the gyroscope dynamically. Following a carefully deduced mathematical calibration model, LGC-Net leverages the depthwise separable convolution to capture the sectional features and reduce the network model parameters. The Large kernel attention is designed to learn the long-range dependencies and feature representation better. The proposed algorithm is evaluated in the EuRoC and TUM-VI datasets and achieves state-of-the-art on the (unseen) test sequences with a more lightweight model structure. The estimated orientation with our LGC-Net is comparable with the top-ranked visual-inertial odometry systems, although it does not adopt vision sensors. We make our method open-source at: https://github.com/huazai665/LGC-Ne

    Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors

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    Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even failure in a matter of seconds. Wireless monitoring systems typically employ duty cycling to reduce power consumption; hence, they will miss such events if they are in power-saving sleep mode when the events occur. This paper develops a demand-based WSS to meet the requirements of sudden event monitoring with minimal power budget and low response latency, without sacrificing high-fidelity measurements or risking a loss of critical information. In the proposed WSS, a programmable event-based switch is implemented utilizing a low-power trigger accelerometer; the switch is integrated in a high-fidelity sensor platform. Particularly, the approach can rapidly turn on the WSS upon the occurrence of a sudden event and seamlessly transition from low-power acceleration measurement to high-fidelity data acquisition. The capabilities of the proposed WSS are validated through laboratory and field experiments. The results show that the proposed approach is able to capture the occurrence of sudden events and provide high-fidelity data for structural condition assessment in an efficient manner

    Providing location everywhere

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    Anacleto R., Figueiredo L., Novais P., Almeida A., Providing Location Everywhere, in Progress in Artificial Intelligence, Antunes L., Sofia Pinto H. (eds), Lecture Notes in Artificial Intelligence 7026, Springer-Verlag, ISBN 978-3-540-24768-2, (Proceedings of the 15th Portuguese conference on Artificial Intelligence - EPIA 2011, Lisboa, Portugal), pp 15-28, 2011.The ability to locate an individual is an essential part of many applications, specially the mobile ones. Obtaining this location in an open environment is relatively simple through GPS (Global Positioning System), but indoors or even in dense environments this type of location system doesn’t provide a good accuracy. There are already systems that try to suppress these limitations, but most of them need the existence of a structured environment to work. Since Inertial Navigation Systems (INS) try to suppress the need of a structured environment we propose an INS based on Micro Electrical Mechanical Systems (MEMS) that is capable of, in real time, compute the position of an individual everywhere

    Assuring measurement traceability to ATE systems for MEMS temperature sensors testing and calibration

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    In the framework of an EMPIR joint research project (MET4FoF - Metrology for Factory of Future), a facility is being developed to provide in-situ measurement traceability to next-generation of Automated Test Equipment (ATE) systems used in MEMS temperature sensors testing and calibration. The above measurement traceability concepts are demonstrated in a testbed developed by SPEA in collaboration with INRIM and IPQ. The experimental work comprises both the factory-side implementation and the laboratory-side developments of a special calibration facility, to cover the temperature range between approximately -60 °C and 200 °C. On the factory side, SPEA develops a novel ATE prototype system, based on the concepts of good metrology practice, with the possibility to calibrate/validate in-situ the electronic circuitry and the on-board reference temperature sensors. The novel ATE prototype implements: • An improved temperature control system, with a new design of heaters, temperature sensors and MEMS temperature conditioning features. • A CPU software/firmware improvements to store sensors’ calibration coefficients and allow a “one-touch calibration” feature (i.e. a fully automatic process able to perform a comparison calibration of the ATE on-board reference temperature sensors). • An assessment of thermal conditions (homogeneity, heat losses, boundary effects) to estimate temperature calibration uncertainty. • A so-called “reference fixture”, i.e. an instrumented sensor socket equipped with a network of laboratory-calibrated reference sensors. On the laboratory side, INRIM develops calibration facilities and measurements methods to provide traceable temperature and electrical measurements to the above ATE systems. A custom equipment is developed to accommodate the sensors belonging to the reference fixture in order to calibrate them by comparison in a thermostatic bath. IPQ deals with the numerical simulation, by means of a 3D model of the temperature uniformity of the thermal chuck i.e. the ATE component providing the thermal stimulus to the MEMS under test. The simulation data will be used to help the SPEA hardware designer to improve the type, number and position of reference sensors on the thermal chuck to provide a more reliable and metrologically characterized thermal stimulus. The final paper will describe how an ATE machine works and in which parts it consists and how it is modified to reach the final goal. Furthermore, simulation data will be cross-compared with experimental data coming from metrological characterization before and after the ATE improvements in order to demonstrate their effectiveness. Also the method to assure traceability in large-scale temperature MEMS testing will be detailed and an example of application will be reported. Finally, it is expected that the outcome of this work will impact the quality and reliability of the MEMS sensors largely used in consumer electronics and will extend the calibration capability provided by INRIM to such an expanding industrial sector

    Operational modal analysis of a highway bridge using acquired data of different accelerometers

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    Les aplicacions de monitorització de la salut estructural (SHM) estan rebent cada vegada més atenció, això és perquè mitjançant la seva aplicació es pot aconseguir la detecció i caracterització dels danys en una fase de prevenció. A més, SHM és un procés dissenyat per proporcionar informació precisa i exacta relacionada amb l'estat i rendiment d'una estructura al llarg del temps. Cal destacar que aquest monitoratge també pot ajudar en els processos de prendre de decisions per optimitzar el funcionament, proporcionar manteniment, reparar i, possiblement, substituir elements estructurals. Un sistema de monitoratge típic comprèn una xarxa de sensors encarregats de mesurar diferents paràmetres rellevants. Tot i això, l'elevat cost dels sensors comercials representa una limitació crítica per a la seva implantació. Per superar el cost elevat de la instrumentació, es poden desenvolupar i validar sensors de baix cost per a aplicacions de SHM. En aquest treball de fi de màster es fa una campanya experimental per a l'Anàlisi Modal Operativa (OMA) d'un pont de carretera utilitzant dos acceleròmetres: un prototip de baix cost (LARA: Low-cost Adaptable Reliable Accelerometer) i un de comercial (PCB 907A61). Amb la finalitat d'avaluar la fiabilitat de les dades adquirides per LARA i validar-les com a acceleròmetres de baix cost per a la monitorització de la salut estructural, es van instal·lar aquests sensors en un pont de carretera ubicat a Andoain, País Basc. Els resultats obtinguts per a cada tipus d'acceleròmetre es van comparar amb el Criteri de Garantia Modal (MAC) i es va avaluar la diferència entre les freqüències pròpies calculades. A més, els paràmetres modals obtinguts durant la campanya experimental es van fer servir per calibrar un model d'elements finits del pont en estudi. Aquest procés es va fer per obtenir una representació més propera a l'estat real de l'estructura.Las aplicaciones de monitorización de la salud estructural (SHM) están recibiendo cada vez más atención, esto se debe a que mediante su aplicación se puede lograr la detección y caracterización de los daños en una fase de prevención. Además, SHM es un proceso diseñado para proporcionar información precisa y exacta relacionada con el estado y el rendimiento de una estructura a lo largo del tiempo. Cabe destacar que esta monitorización también puede ayudar en los procesos de toma de decisiones para optimizar el funcionamiento, proporcionar mantenimiento, reparar y, posiblemente, sustituir elementos estructurales. Un sistema de monitorización típico comprende una red de sensores encargados de medir diferentes parámetros relevantes. Sin embargo, el elevado coste de los sensores comerciales representa una limitación crítica para su implantación. Para superar el elevado coste de la instrumentación, se pueden desarrollar y validar sensores de bajo coste para aplicaciones de SHM. En este trabajo de fin de máster se realiza una campaña experimental para el Análisis Modal Operativo (OMA) de un puente de carretera utilizando dos acelerómetros: un prototipo de bajo coste (LARA: Low-cost Adaptable Reliable Accelerometer) y uno comercial (PCB 907A61). Con la finalidad de evaluar la fiabilidad de los datos adquiridos por LARA y validarlos como acelerómetros de bajo coste para la monitorización de la salud estructural, se instalaron estos sensores en un puente de carretera ubicado en Andoain, País Vasco. Los resultados obtenidos para cada tipo de acelerómetro se compararon bajo el Criterio de Garantía Modal (MAC) y se evaluó la diferencia entre las frecuencias propias calculadas. Además, los parámetros modales obtenidos durante la campaña experimental se utilizaron para calibrar un modelo de elementos finitos del puente en estudio. Este proceso se realizó a fin de obtener una representación más cercana al estado real de la estructura.Structural health monitoring (SHM) applications are increasingly getting more attention. It is due to the fact that through their implementation, the detection and characterization of damage during a prevention phase can be achieved. Furthermore, SHM is a process designed to provide precise and accurate information associated with the condition and performance of a structure over time. It should be noted that SHM can also help with decision-making processes to optimize the operation, provide maintenance, repair, and possibly replace structural elements. A typical monitoring system comprises a network of sensors in charge of measuring different relevant parameters. However, the high cost of commercial sensors can be a critical limitation for their implementation. To overcome the high cost of instrumentation, low-cost sensors can be developed and validated for SHM applications. This Master's thesis carries out an experimental campaign for the Operational Modal Analysis (OMA) of a highway bridge using two accelerometers: a low-cost prototype (LARA: Low-cost Adaptable Reliable Accelerometer) and a commercial one (PCB 907A61). In order to evaluate the reliability of the data acquired by LARA and to validate it as a low-cost accelerometer for structural health monitoring, these accelerometers were mounted on a highway bridge located in Andoain, Basque Country. The results obtained for each type of accelerometer are compared by using the Modal Assurance Criteria (MAC) and assessing the difference between the analyzed eigenfrequencies. Moreover, the modal parameters obtained during the experimental campaign are used to calibrate a finite element model of this bridge. This analytical model is calibrated to have a closer representation of the real state of the structure

    Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning

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    The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected
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