SEARCH · Search NASA

Results for “embedded sensors”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

NASA NTRS2008

The Vector Electric Field Instrument on the C/NOFS Satellite

We provide an overview of the Vector Electric Field Instrument (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite, a mission designed to understand, model, and forecast the presence of equatorial ionospheric irregularities. VEFI is a NASA GSFC instrument designed 1) to investigate the role of the ambient electric fields in initiating nighttime ionospheric density depletions and turbulence; 2) to determine the electric fields associated with abrupt, large amplitude, density depletions and 3) to quantify the spectrum of the wave electric fields and plasma densities (irregularities) associated with density depletions or Equatorial Spread-F. The VEFI instrument includes a vector electric field double probe detector, a Langmuir trigger probe, a flux gate magnetometer, a lightning detector and associated electronics. The heart of the instrument is the set of double probe detectors designed to measure DC and AC electric fields using 6 identical, mutually orthogonal, deployable 9.5 m booms tipped with 10 cm diameter spheres containing embedded preamplifiers. A description of the instrument and its sensors will be presented. If available, representative measurements will be provided.

Pfaff, R.↗

NASA NTRS2012

Interactive robot control system and method of use

A robotic system includes a robot having joints, actuators, and sensors, and a distributed controller. The controller includes command-level controller, embedded joint-level controllers each controlling a respective joint, and a joint coordination-level controller coordinating motion of the joints. A central data library (CDL) centralizes all control and feedback data, and a user interface displays a status of each joint, actuator, and sensor using the CDL. A parameterized action sequence has a hierarchy of linked events, and allows the control data to be modified in real time. A method of controlling the robot includes transmitting control data through the various levels of the controller, routing all control and feedback data to the CDL, and displaying status and operation of the robot using the CDL. The parameterized action sequences are generated for execution by the robot, and a hierarchy of linked events is created within the sequence.

Sanders, Adam M.↗

NASA NTRS2001

Raman and FTIR Studies of Silicon Carbide Surface Damage from Palladium Implantation in Presence of Hydrogen

The ion implantation in a crystal such as silicon carbide will cause both damage in the ion track and in the substrate at the end of the ion track. We used both keV, and MeV Pd ions in fabricating electronic chemical sensors in silicon carbide, which can operate at elevated temperatures. In order to study the feasibility of fabricating an optical chemical sensor (litmus sensor), we need to understand the optical behavior of the embedded damage in the presence of hydrogen, as well as the potential chemical interaction of silicon carbide broken lattice bonds with the hydrogen dissociated from gas by palladium. Implanted samples of silicon carbide were studied using both Raman spectroscopy and FTIR (Fourier Transform-Infrared). The results of this work will be presented during the meeting.

Muntele, I.↗

NASA NTRS2003

Electrical-Impedance-Based Ice-Thickness Gauges

Langley Research Center has developed electrical-impedance-based ice-thickness gauges and is seeking partners and collaborators to commercialize them. When used as parts of active monitoring and diagnostic systems, these gauges make it possible to begin deicing or to take other protective measures before ice accretes to dangerous levels. These gauges are inexpensive, small, and simple to produce. They can be adapted to use on a variety of stationary and moving structures that are subject to accumulation of ice. Examples of such structures include aircraft, cars, trucks, ships, buildings, towers, power lines (see figure), power-generating equipment, water pipes, freezer compartments, and cooling coils. A gauge of this type includes a temperature sensor and two or more pairs of electrically insulated conductors embedded in a surface on which ice could accumulate. The electrical impedances of the pairs of conductors vary with the thickness of any ice that may be present. Somewhat more specifically, when the pairs of conductors are spaced appropriately, the ratio between their impedances is indicative of the thickness of the ice. Therefore, the gauge includes embedded electronic circuits that measure the electrical impedances, plus circuits that process the combination of temperature and impedance measurements to determine whether ice is present and, if so, how thick it is. Of course, in the processing of the impedance measurements, the temperature measurements help the circuitry to distinguish between liquid water and ice. The basic design of a gauge of this type can be adapted to local conditions. For example, if there is a need to monitor ice over a wide range of thickness, then the gauge can include more than two sets of conductors having various spacings.

Weinstein, Leonard↗

NASA NTRS2013

Synthetic Foveal Imaging Technology

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Monacos, Steve P.↗

NASA NTRS2013

Distributed Prognostics and Health Management with a Wireless Network Architecture

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the prognostics task is over, and after appropriate actions have been taken, all CEs return to their original default configuration. Wireless technology-based implementation would ensure more flexibility in terms of sensor placement. It would also allow more sensors to be deployed because the overhead related to weights of wired systems is not present. Distributed architectures are furthermore generally robust with regard to recovery from node failures.

Goebel, Kai↗

NASA NTRS2011

Compliant Tactile Sensors

Tactile sensors are currently being designed to sense interactions with human hands or pen-like interfaces. They are generally embedded in screens, keyboards, mousepads, and pushbuttons. However, they are not well fitted to sense interactions with all kinds of objects. A novel sensor was originally designed to investigate robotics manipulation where not only the contact with an object needs to be detected, but also where the object needs to be held and manipulated. This tactile sensor has been designed with features that allow it to sense a large variety of objects in human environments. The sensor is capable of detecting forces coming from any direction. As a result, this sensor delivers a force vector with three components. In contrast to most of the tactile sensors that are flat, this one sticks out from the surface so that it is likely to come in contact with objects. The sensor conforms to the object with which it interacts. This augments the contact's surface, consequently reducing the stress applied to the object. This feature makes the sensor ideal for grabbing objects and other applications that require compliance with objects. The operational range of the sensor allows it to operate well with objects found in peoples' daily life. The fabrication of this sensor is simple and inexpensive because of its compact mechanical configuration and reduced electronics. These features are convenient for mass production of individual sensors as well as dense arrays. The biologically inspired tactile sensor is sensitive to both normal and lateral forces, providing better feedback to the host robot about the object to be grabbed. It has a high sensitivity, enabling its use in manipulation fingers, which typically have low mechanical impedance in order to be very compliant. The construction of the sensor is simple, using inexpensive technologies like silicon rubber molding and standard stock electronics.

Torres-Jara, Eduardo R.↗

NASA NTRS1990

Fiber optic smart structures and skins II; Proceedings of the Meeting, Boston, MA, Sept. 5-8, 1989

The present conference on embedded fiber-optics incorporating 'smart' structural systems and structural surfaces discusses topics in the nature and current status of university- and government-sponsored smart-structure development programs, manufacturing and cure-monitoring for composite smart structures, smart-structure damage assessment, smart-structure actuators, and smart-structure sensors and components. Attention is given to fiber-optic sensor selection, the optical properties of curing epoxies, the automated production of smart structures, damage-detection in composites with embedded fiber-optic interferometers, fiber-optic strain and impact sensors, dynamically-tunable smart composites, smart structures incorporating artificial neural networks, active structural acoustic control with smart structures, and fiber-optic shape sensing for flexible structures.

Udd, Eric↗

NASA NTRS2017

Damage Detection Sensor System for Aerospace and Multiple Applications

The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.

Williams, M.↗

NASA NTRS2017

Advanced Wireless Sensor Nodes - MSFC

NASA field center Marshall Space Flight Center (Huntsville, AL), has invested in advanced wireless sensor technology development. Developments for a wireless microcontroller back-end were primarily focused on the commercial Synapse Wireless family of devices. These devices have many useful features for NASA applications, good characteristics and the ability to be programmed Over-The-Air (OTA). The effort has focused on two widely used sensor types, mechanical strain gauges and thermal sensors. Mechanical strain gauges are used extensively in NASA structural testing and even on vehicle instrumentation systems. Additionally, thermal monitoring with many types of sensors is extensively used. These thermal sensors include thermocouples of all types, resistive temperature devices (RTDs), diodes and other thermal sensor types. The wireless thermal board will accommodate all of these types of sensor inputs to an analog front end. The analog front end on each of the sensors interfaces to the Synapse wireless microcontroller, based on the Atmel Atmega128 device. Once the analog sensor output data is digitized by the onboard analog to digital converter (A/D), the data is available for analysis, computation or transmission. Various hardware features allow custom embedded software to manage battery power to enhance battery life. This technology development fits nicely into using numerous additional sensor front ends, including some of the low-cost printed circuit board capacitive moisture content sensors currently being developed at Auburn University.

Varnavas, Kosta↗

NASA NTRS2017

IMAPS Device Packaging Conference 2017 - Engineered Micro Systems & Devices Track

Varnavas, Kosta↗

NASA NTRS2009

Spacesuit Data Display and Management System

A prototype embedded avionics system has been designed for the next generation of NASA extra-vehicular-activity (EVA) spacesuits. The system performs biomedical and other sensor monitoring, image capture, data display, and data transmission. An existing NASA Phase I and II award winning design for an embedded computing system (ZIN vMetrics - BioWATCH) has been modified. The unit has a reliable, compact form factor with flexible packaging options. These innovations are significant, because current state-of-the-art EVA spacesuits do not provide capability for data displays or embedded data acquisition and management. The Phase 1 effort achieved Technology Readiness Level 4 (high fidelity breadboard demonstration). The breadboard uses a commercial-grade field-programmable gate array (FPGA) with embedded processor core that can be upgraded to a space-rated device for future revisions.

Hall, David G.↗

NASA NTRS2004

Hybrid Piezoelectric/Fiber-Optic Sensor Sheets

Hybrid piezoelectric/fiber-optic (HyPFO) sensor sheets are undergoing development. They are intended for use in nondestructive evaluation and long-term monitoring of the integrity of diverse structures, including aerospace, aeronautical, automotive, and large stationary ones. It is anticipated that the further development and subsequent commercialization of the HyPFO sensor systems will lead to economic benefits in the form of increased safety, reduction of life-cycle costs through real-time structural monitoring, increased structural reliability, reduction of maintenance costs, and increased readiness for service. The concept of a HyPFO sensor sheet is a generalization of the concept of a SMART Layer(TradeMark), which is a patented device that comprises a thin dielectric film containing an embedded network of distributed piezoelectric actuator/sensors. Such a device can be mounted on the surface of a metallic structure or embedded inside a composite-material structure during fabrication of the structure. There is has been substantial interest in incorporating sensors other than piezoelectric ones into SMART Layer(TradeMark) networks: in particular, because of the popularity of the use of fiber-optic sensors for monitoring the "health" of structures in recent years, it was decided to incorporate fiber-optic sensors, giving rise to the concept of HyPFO devices.

Lin, Mark↗

NASA NTRS2022

Fabrication and Testing of a Novel Ceramic-Based Additively Manufactured Humidity Sensor

A material capable of detecting minute changes in ambient humidity via a change in its electrical properties is critical to enabling the success of vapor-sensitive components on Earth and abroad. Manufacturing of these hydrophilic materials currently follows an extensive process of heat treating focused on removing the solvent and organic vehicle. This research aims to reduce the complexity of manufacturing these novel sensors by eliminating the high-temperature (>850 °C) processing stages. A method based on printing a polymer embedded with hydrophilic nanoparticles is accomplished through selected additively manufactured methods. This research branches into the elimination of physical spare parts with the ability to print highly sensitive in-situ sensors, reducing the environmental footprint in space-critical environments like the International Space Station (ISS).

sensor↗

NASA NTRS2021

Overview of Dragonfly Entry Aerosciences Measurements (DrEAM)

NASA Ames Research Center (ARC) leads the Dragonfly Entry Aerosciences Measurements (DrEAM) project, which is an aeroshell instrumentation suite on the Dragonfly mission that fulfills the Engineering Science Investigation requirement for the New Frontiers mission. NASA ARC is partnering with NASA Langley Research Center (LaRC) and the German Aerospace Center (DLR) to provide a comprehensive sensor suite, including a DLR-provided Data Acquisition System (DAS). DrEAM will provide key aerothermodynamic data and performance analysis for Dragonfly’s forebody and backshell Thermal Protection System (TPS). Titan’s atmosphere predominantly consists of ni-trogen (~98% by mole) with small amounts of me-thane (~2% by mole) and other trace gases. CN is a strong radiator, and is found in nonequilibrium con-centrations for Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a diffi-cult task. Prompted by the Huygens mission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experienced by the probe during Titan entry [1]. How-ever, the Huygens probe carried no heatshield instru-mentation. Therefore, the DrEAM sensor suite will sig-nificantly advance the state-of-the-art not only by documenting the environment and performance of Dragonfly’s entry system but also by making key in situ measurements in Titan’s atmosphere for the first time. Aerothermal environments and TPS response will be measured using sensors whose flight heritage is tak-en from the Mars Entry, Descent, and Landing In-strumentation 2 (MEDLI2) thermocouple plugs and the COMbined Aerothermal and Radiometer Sensor (COMARS) suite [2], with the latter supplied by DLR. The MEDLI2 project used embedded thermocouples to directly measure the in-depth TPS temperature-time history at several locations on the heat shield and backshell of the Mars 2020 entry vehicle. These tem-perature measurements, in turn, can be used to infer surface environments via an inverse analysis proce-dure analogous to that used for MEDLI. For DrEAM, the thermocouple plug subsystem will be known as Dragonfly Sensors for Aero-Thermal Reconstruction (DragSTR). On Schiaparelli, the COMARS suite in-cluded three total surface-mounted heat flux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as the COmbined Sensor System for Titan Atmosphere (COSSTA). Since the methane concentration in the Titan atmos-phere is directly proportional to the radiative heat flux, the COSSTA measurements will be used to reduce the current uncertainty in the methane volume fraction. Atmospheric density measurements and capsule aero-dynamic data will be obtained through the onboard Inertial Measurement Unit (IMU), supplemented by pressure transducers similar to those used by the MEDLI and MEDLI2 projects. The DrEAM pressure sensors will be known as the Dragonfly Atmospheric Flight Transducers. (DrAFT). The pressure measure-ments, when combined with data from the on-board IMU, will allow for reconstruction of such quantities as vehicle Mach number, freestream density, and atmos-pheric winds. DrAFT measurements will enhance Dragonfly trajectory reconstruction and enable a sepa-ration of the aerodynamics from the atmosphere, as was done for MEDLI [3] and is currently in process for the MEDLI2 flight data set.

EDL↗

NASA NTRS1992

Control of sound radiation with active/adaptive structures

Recent research is discussed in the area of active structural acoustic control with active/adaptive structures. Progress in the areas of structural acoustics, actuators, sensors, and control approaches is presented. Considerable effort has been given to the interaction of these areas with each other due to the coupled nature of the problem. A discussion is presented on actuators bonded to or embedded in the structure itself. The actuators discussed are piezoceramic actuators and shape memory alloy actuators. The sensors discussed are optical fiber sensors, Nitinol fiber sensors, piezoceramics, and polyvinylidene fluoride sensors. The active control techniques considered are state feedback control techniques and least mean square adaptive algorithms. Results presented show that significant progress has been made towards controlling structurally radiated noise by active/adaptive means applied directly to the structure.

Fuller, C. R.↗

NASA NTRS2011

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗

NASA NTRS1992

Physical retrieval of precipitation water contents using multisensor microwave data and model constraints

A physical retrieval method is proposed for estimating precipitation water distributions and other geophysical parameters from the Special Sensor Microwave/Imager (SSM/I) data. In the proposed method, sensor antenna functions are explicitly included to accommodate varying channel resolution. An embedded one-dimensional cloud model is utilized to generate vertical distributions of precipitating and nonprecipitating water, and spectral solutions are sought for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The method allows the incorporation of measurements from SSM/T and geostationary infrared measurements in addition to SSM/I data, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Olson, William S.↗