Study of First-Order Thermal Sigma-Delta Architecture for Convective Accelerometers

This paper presents the study of an original closed-loop conditioning approach for fully-integrated convective inertial sensors. The method is applied to an accelerometer manufactured on a standard CMOS technology using an auto-aligned bulk etching step. Using the thermal behavior of the sensor as a summing function, a first order sigma-delta modulator is built. This "electro-physical" modulator realizes an analog-to-digital conversion of the signal. Besides the feedback scheme should improve the sensor performance.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Tri-axis convective accelerometer with closed-loop heat source

In this paper, we report the details and findings of a study on tri-axis convective accelerometer, which is designed with the closed-loop type heat source and thermal sensing hotwire elements. The closed-loopheat source enhances the convective flow to the central part where a hotwire is placed to measure the vertical component of acceleration. The simulation was conducted using numerical analysis, and the devicewas prototyped by additive manufacturing. The device, functioning as a tilt sensor and an accelerometer,was tested up to acceleration of 20 g. The experiments were successfully conducted and the experimental results agreed reasonably with those obtained by numerical analysis. The results demonstrated that the closed-loop heat source could reduce the cross effect between the acceleration components. The scalefactor and cross-sensitivity had the values of 0.26 micro�V/g and 1.2%, respectively. The cross-sensitivity andthe effects of heating power were also investigated in this study

Modeling and Experimental Study on Characterization of Micromachined Thermal Gas Inertial Sensors

Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication

Sensing Movement: Microsensors for Body Motion Measurement

Recognition of body posture and motion is an important physiological function that can keep the body in balance. Man-made motion sensors have also been widely applied for a broad array of biomedical applications including diagnosis of balance disorders and evaluation of energy expenditure. This paper reviews the state-of-the-art sensing components utilized for body motion measurement. The anatomy and working principles of a natural body motion sensor, the human vestibular system, are first described. Various man-made inertial sensors are then elaborated based on their distinctive sensing mechanisms. In particular, both the conventional solid-state motion sensors and the emerging non solid-state motion sensors are depicted. With their lower cost and increased intelligence, man-made motion sensors are expected to play an increasingly important role in biomedical systems for basic research as well as clinical diagnostics

MEMS Accelerometers

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

Transducer applications, a compilation

The characteristics and applications of transducers are discussed. Subjects presented are: (1) thermal measurements, (2) liquid level and fluid flow measurements, (3) pressure transducers, (4) stress-strain measurements, (5) acceleration and velocity measurements, (6) displacement and angular rotation, and (7) transducer test and calibration methods

Multisensor MEMS for temperature, relative humidity, and high-g shock monitoring

The use of MEMS (micro-electro-mechanical system) sensors in multiple applications of environmental monitoring help to fill the need of a small scale, low power monitoring and sensing applications. In this design, the use of single-die multiple MEMS sensors to monitor ambient temperature, relative humidity, and accelerative high-g shock were developed and tested. In addition to the sensors, signal conditioning circuits were developed for outputting the sensor data into a microcontroller to analyze and process the signals into useful information for human operators to analyze. The three sensors were fabricated using a bulk micro-machined process on 100mm silicon wafers developed in the RIT SMFL. This work extends previous work on a multisensor from a year earlier. Ion implantation is now used to tune doping levels. To help reduce cross-talk between sensors, p-wells were introduced to aid in substrate isolation. A parallel plate humidity sensor was developed, bringing the need to develop in-line processing of polyimide. Lastly, the one-axis shock sensor is upgraded into a three-axis shock sensor. The temperature sensor is made using a PN diode, utilizing the temperature dependence of the forward bias voltage drop from the Shockley diode equation, corresponding to -2.2mV/°C response over a range of -50°C to 150°C for the application operation range. Signal conditioning is a constant current mode operation, measuring the change in voltage drop across the diode. The relative humidity sensor is formed from one of two designs; an interdigitated comb-finger capacitor or a parallel plate capacitor. Polyimide was used as the dielectric material due to linear diffusion properties of water vapor to relative humidity. While the comb-finger sensor was coated with polyimide post-processing, a new thin film processing and integration technique was developed for the first time here at RIT for the parallel plate sensor. Due to the small levels of capacitive change in the range of 5% to 95% relative humidity, the sensor\u27s capacitive measurement is run through an RC astable multivibrator circuit to produce an RC square wave. From the frequency of this wave, the capacitance, and thus the relative humidity can be computed by the microcontroller

User Needs, Benefits, and Integration of Robotic Systems in a Space Station Laboratory

The methodology, results and conclusions of all tasks of the User Needs, Benefits, and Integration Study (UNBIS) of Robotic Systems in a Space Station Laboratory are summarized. Study goals included the determination of user requirements for robotics within the Space Station, United States Laboratory. In Task 1, three experiments were selected to determine user needs and to allow detailed investigation of microgravity requirements. In Task 2, a NASTRAN analysis of Space Station response to robotic disturbances, and acceleration measurement of a standard industrial robot (Intelledex Model 660) resulted in selection of two ranges of microgravity manipulation: Level 1 (10-3 to 10-5 G at greater than 1 Hz) and Level 2 (less than equal 10-6 G at 0.1 Hz). This task included an evaluation of microstepping methods for controlling stepper motors and concluded that an industrial robot actuator can perform milli-G motion without modification. Relative merits of end-effectors and manipulators were studied in Task 3 in order to determine their ability to perform a range of tasks related to the three microgravity experiments. An Effectivity Rating was established for evaluating these robotic system capabilities. Preliminary interface requirements for an orbital flight demonstration were determined in Task 4. Task 5 assessed the impact of robotics

The First Comparison Between Swarm-C Accelerometer-Derived Thermospheric Densities and Physical and Empirical Model Estimates

The first systematic comparison between Swarm-C accelerometer-derived thermospheric density and both empirical and physics-based model results using multiple model performance metrics is presented. This comparison is performed at the satellite's high temporal 10-s resolution, which provides a meaningful evaluation of the models' fidelity for orbit prediction and other space weather forecasting applications. The comparison against the physical model is influenced by the specification of the lower atmospheric forcing, the high-latitude ionospheric plasma convection, and solar activity. Some insights into the model response to thermosphere-driving mechanisms are obtained through a machine learning exercise. The results of this analysis show that the short-timescale variations observed by Swarm-C during periods of high solar and geomagnetic activity were better captured by the physics-based model than the empirical models. It is concluded that Swarm-C data agree well with the climatologies inherent within the models and are, therefore, a useful data set for further model validation and scientific research.Comment: https://goo.gl/n4QvU