Community Seismic Network

The article describes the design of the Community Seismic Network, which is a dense open seismic network based on low cost sensors. The inputs are from sensors hosted by volunteers from the community by direct connection to their personal computers, or through sensors built into mobile devices. The server is cloud-based for robustness and to dynamically handle the load of impulsive earthquake events. The main product of the network is a map of peak acceleration, delivered within seconds of the ground shaking. The lateral variations in the level of shaking will be valuable to first responders, and the waveform information from a dense network will allow detailed mapping of the rupture process. Sensors in buildings may be useful for monitoring the state-of-health of the structure after major shaking

Delayed pull-in transitions in overdamped MEMS devices

We consider the dynamics of overdamped MEMS devices undergoing the pull-in instability. Numerous previous experiments and numerical simulations have shown a significant increase in the pull-in time under DC voltages close to the pull-in voltage. Here the transient dynamics slow down as the device passes through a meta-stable or bottleneck phase, but this slowing down is not well understood quantitatively. Using a lumped parallel-plate model, we perform a detailed analysis of the pull-in dynamics in this regime. We show that the bottleneck phenomenon is a type of critical slowing down arising from the pull-in transition. This allows us to show that the pull-in time obeys an inverse square-root scaling law as the transition is approached; moreover we determine an analytical expression for this pull-in time. We then compare our prediction to a wide range of pull-in time data reported in the literature, showing that the observed slowing down is well captured by our scaling law, which appears to be generic for overdamped pull-in under DC loads. This realization provides a useful design rule with which to tune dynamic response in applications, including state-of-the-art accelerometers and pressure sensors that use pull-in time as a sensing mechanism. We also propose a method to estimate the pull-in voltage based only on data of the pull-in times.Comment: 17 page

Lightweight thermal compensation technique for MEMS capacitive accelerometer oriented to quasi-static measurements

The application of MEMS capacitive accelerometers is limited by its thermal dependence, and each accelerometer must be individually calibrated to improve its performance. In this work, a light calibration method based on theoretical studies is proposed to obtain two characteristic parameters of the sensor’s operation: the temperature drift of bias and the temperature drift of scale factor. This method requires less data to obtain the characteristic parameters, allowing a faster calibration. Furthermore, using an equation with fewer parameters reduces the computational cost of compensation. After studying six accelerometers, model LIS3DSH, their characteristic parameters are obtained in a temperature range between 15 °C and 55 °C. It is observed that the Temperature Drift of Bias (TDB) is the parameter with the greatest influence on thermal drift, reaching 1.3 mg/°C. The Temperature Drift of Scale Factor (TDSF) is always negative and ranges between 0 and −400 ppm/°C. With these parameters, the thermal drifts are compensated in tests with 20 °C of thermal variation. An average improvement of 47% was observed. In the axes where the thermal drift was greater than 1 mg/°C, the improvement was greater than 80%. Other sensor behaviors have also been analyzed, such as temporal drift (up to 1 mg/h for three hours) and self-heating (2–3 °C in the first hours with the corresponding drift). Thermal compensation has been found to reduce the effect of the latter in the first hours after power-up of the sensor by 43%

Gyroless Nanosatellite Attitude Determination Using an Array of Spatially Distributed Accelerometers

The low size and budget of typical nanosatellite missions limit the available sensors for attitude estimation. Relatively high noise MEMS gyroscopes often must be employed when accurate knowledge of the spacecraft’s angular velocity is necessary for attitude determination and control. This thesis derived and tested in simulation the “Virtual Gyroscope” algorithm, which replaced a standard gyroscope with an array of spatially distributed accelerometers for a 1U CubeSat mission. A MEMS accelerometer model was developed and validated using Root Allan Variance, and the Virtual Gyroscope was tested both in the open loop configuration and as a replacement for a gyroscope in a Multiplicative Extended Kalman Filter. It was found that the quality of the Virtual Gyroscope’s rate measurement improved with a larger and higher quality array, but the error in the estimate was very large. The low signal-to-noise ratio and the unknown bias in the accelerometers caused the angular velocity estimate from the accelerometer array to be too poor for use in the propagation step of the Kalman filter. The Kalman filter performed better with attitude measurements alone than with the Virtual Gyroscope, even when the attitude were delivered at a low rate with added noise. Overall, the current Virtual Gyroscope algorithm that is presented in this thesis is not suitable to replace a MEMS gyroscope in a nanosatellite mission, although there is room for future improvements using bias prediction for the individual accelerometers in the array

High-accuracy Motion Estimation for MEMS Devices with Capacitive Sensors

With the development of micro-electro-mechanical system (MEMS) technologies, emerging MEMS applications such as in-situ MEMS IMU calibration, medical imaging via endomicroscopy, and feedback control for nano-positioning and laser scanning impose needs for especially accurate measurements of motion using on-chip sensors. Due to their advantages of simple fabrication and integration within system level architectures, capacitive sensors are a primary choice for motion tracking in those applications. However, challenges arise as often the capacitive sensing scheme in those applications is unconventional due to the nature of the application and/or the design and fabrication restrictions imposed, and MEMS sensors are traditionally susceptible to accuracy errors, as from nonlinear sensor behavior, gain and bias drift, feedthrough disturbances, etc. Those challenges prevent traditional sensing and estimation techniques from fulfilling the accuracy requirements of the candidate applications. The goal of this dissertation is to provide a framework for such MEMS devices to achieve high-accuracy motion estimation, and specifically to focus on innovative sensing and estimation techniques that leverage unconventional capacitive sensing schemes to improve estimation accuracy. Several research studies with this specific aim have been conducted, and the methodologies, results and findings are presented in the context of three applications. The general procedure of the study includes proposing and devising the capacitive sensing scheme, deriving a sensor model based on first principles of capacitor configuration and sensing circuit, analyzing the sensor’s characteristics in simulation with tuning of key parameters, conducting experimental investigations by constructing testbeds and identifying actuation and sensing models, formulating estimation schemes is to include identified actuation dynamics and sensor models, and validating the estimation schemes and evaluating their performance against ground truth measurements. The studies show that the proposed techniques are valid and effective, as the estimation schemes adopted either fulfill the requirements imposed or improve the overall estimation performance. Highlighted results presented in this dissertation include a scale factor calibration accuracy of 286 ppm for a MEMS gyroscope (Chapter 3), an improvement of 15.1% of angular displacement estimation accuracy by adopting a threshold sensing technique for a scanning micro-mirror (Chapter 4), and a phase shift prediction error of 0.39 degree for a electrostatic micro-scanner using shared electrodes for actuation and sensing (Chapter 5).PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147568/1/davidsky_1.pd

A three-axis accelerometer for measuring heart wall motion

This thesis presents the work carried out in the design, simulation, fabrication and testing of miniaturised three-axis accelerometers. The work was carried out at the Faculty of Science and Engineering at Vestfold University College (Tønsberg, Norway), the MIcroSystems Engineering Centre (MISEC) at Heriot-Watt University and in collaboration with the Interventional Centre at Rikshospitalet University Hospital (Oslo, Norway). The accelerometers presented in this thesis were produced to be stitched to the surface of human hearts. In doing so they are used to measure the heart wall motion of patients that have just undergone heart bypass surgery. Results from studies carried out are presented and prove the concept of using such sensors for the detection of problems that can lead to the failure of heart bypasses. These studies were made possible using commercially available MEMS (MicroElectroMechanical Systems) three-axis accelerometers. However, the overall size of these sensors does not meet the requirements deemed necessary by the medical team (2(W) 2(H) 5(L) mm3) and fabrication activities were necessary to produce custom-made sensors. Design verification and performance modelling were carried out using Finite Element Analysis (FEA) and these results are presented alongside relevant analytical calculations. For fabrication, accelerometer designs were submitted to three foundry processes during the course of the work. The designs utilise the piezoresistive effect for the acceleration sensing and fabrication was carried out by bulk micromachining. Results of the characterisaton of the sensors are presente

Monitoring and Self-diagnosis of Civil Engineering Structures: Classical and Innovative Applications

Eventi estremi come esplosioni o terremoti possono avere un profondo impatto nella sicurezza degli edifici. Le zone sismiche devono convivere con questi tragici eventi, per questo monitorare in maniera continua le condizioni di salute di una struttura è necessario e auspicabile in molti casi. Il monitoraggio strutturale (Structural Health Monitoring – SHM) rappresenta un potente strumento per la valutazione del comportamento dinamico della struttura monitorata. Fino a pochi anni fa queste tecniche erano impiegate prevalentemente in ambito meccanico, aeronautico e nell’ingegneria aerospaziale. Al giorno d’oggi, la riduzione dei costi della strumentazione, sistemi di acquisizione dati di nuova generazione e l’incremento continuo dell’efficienta nelle analisi numeriche hanno reso possibile l’applicazione di queste tecniche anche a strutture civili ordinarie. Le tecniche di monitoraggio strutturale vengono applicate non solo in grandi infrastrutture come ponti, dighe o grattacieli, ma anche in strutture storiche o edifici residenziali. In questo contesto questa tesi tenta di esaminare differenti aspetti del monitoraggio strutturale, in particolar modo riferite a edifici ordinari. Attraverso tecniche Output-Only (Operational Modal Analysis – OMA) sono state monitorate diverse strutture civili con reti di sensori cablate, al fine di ottenere il comportamento dinamico strutturale nelle reali condizioni opertive. Particolare attenzione è stata focalizzata in un altra importante tematica dell’ingegneria strutturale: il danneggiamento strutturale. Attraverso un approccio numerico viene presentato un nuovo metodo per la localizzazione e quantificazione del danno a seguito di un evento sismico. In alternativa alla classica rete cablata, è stato sviluppato un sistema di acquisizione con sensori wireless (Wireless Sensor Network – WSN). I principali risultati ottenuti con questa applicazione vengono riportati nella presente tesi, unitamente al design dei sensori low-cost. Con l’ausilio della sensoristica sviluppata è stato monitorato un edificio storico in muratura, mostrando i risultati positivi ottenuti a seguito della campagna di acquisizione di rumore ambientale (Ambient Vibration Survey -AVS).Extreme events like explosions and earthquakes may have a deep impact on building safety. Seismic regions must live with these tragic events, so that continuous monitoring of structure health conditions is necessary in many cases. Structural Health Monitoring (SHM) represents a powerful tool for the evaluation of dynamic behavior of monitored structures. Until a few years ago these techniques were widely employed especially in mechanical, aeronautical and aerospace engineering. Nowadays, the reduction of equipment costs, the new generation of data acquisition systems, together with the continuous improvement of computational analysis have made it possible to apply SHM also to civil structures without strategic importance. SHM has moved from large infrastructures like bridges, dams and skyscrapers to historical heritage and residential buildings. In this background, the present work tries to examine different aspects of SHM applications, especially referred to ordinary buildings. Using Operational Modal Analysis (OMA) techniques, several civil structures have been monitored through a wired network sensor, in order to obtain the dynamic behavior in operating conditions. The relevant data collection provides a useful tool for calibrating the accuracy and sensitivity of similar SHM case studies. Specific attention is focused in another important issue in civil and in mechanical engineering: detection of structural damages. Through a numerical approach, a new method for damage localization and quantification is proposed. Besides the traditional wired acquisition system a Wireless Sensor Network (WSN) has been developed. The issues related to the usage of low-cost sensors and new generation data acquisition tools for non-destructive structural testing are discussed. Using the WSN an historical masonry building has been monitored, showing the positive results obtained following the Ambient Vibration Survey (AVS)