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This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar radiation on the stringing section, transmits the data to the Transmission Energy Management System, validates its integrity and passes it on to Oncor and ERCOT (Electric Reliability Council of Texas) respective system operations. The iDLR system is automatic and transparent to ERCOT System Operations, i.e., it operates in parallel with all other system status telemetry collected through Supervisory Control and Data Acquisition (SCADA) employed across the company.
The generation of sound by heat has been documented as an “acoustical curiosity” since a Buddhist monk reported the loud tone generated by a ceremonial rice-cooker in his diary, in 1568. Over the last four decades, significant progress has been made in understanding “thermoacoustic processes,” enabling the design of thermoacoustic engines and refrigerators. Motivated by the Fukushima nuclear reactor disaster, we have developed and tested a thermoacoustic engine that exploits the energy-rich conditions in the core of a nuclear reactor to provide core condition information to the operators without a need for external electrical power. The heat engine is self-powered and can wirelessly transmit the temperature and reactor power level by generation of a pure tone which can be detected outside the reactor. We report here the first use of a fission-powered thermoacoustic engine capable of serving as a performance and safety sensor in the core of a research reactor and present data from the hydrophones in the coolant (far from the core) and an accelerometer attached to a structure outside the reactor. These measurements confirmed that the frequency of the sound produced indicates the reactor’s coolant temperature and that the amplitude (above an onset threshold) is related to the reactor’s operating power level. Furthermore, these signals can be detected even in the presence of substantial background noise generated by the reactor’s fluid pumps.
The NASA Small Explorer Data System (SEDS), a space flight data system developed to support the Small Explorer (SMEX) project, is addressed. The system was flown on the Solar Anomalous Magnetospheric Particle Explorer (SAMPEX) SMEX mission, and with reconfiguration for different requirements will fly on the X-ray Timing Explorer (XTE) and the Tropical Rainfall Measuring Mission (TRMM). SEDS is also foreseen for the Hubble repair mission. Its name was changed to Spacecraft Data System (SDS) in view of expansions. Objectives, SDS hardware, and software are described. Each SDS box contains two computers, data storage memory, uplink (command) reception circuitry, downlink (telemetry) encoding circuitry, Instrument Telemetry Controller (ITC), and spacecraft timing circuitry. The SDS communicates with other subsystems over the MIL-STD-1773 data bus. The SDS software uses a real time Operating System (OS) and the C language. The OS layer, communications and scheduling layer, application task layer, and diagnostic software, are described. Decisions on the use of advanced technologies, such as ASIC's (Application Specific Integrated Circuits) and fiber optics, led to technical improvements, such as lower power and weight, without increasing the risk associated with the data system. The result was a successful SAMPEX development, integration and test, and mission using SEDS, and the upgrading of that system to SDS for TRMM and XTE.
The computational infrastructure of the International Space Station (ISS) is a dynamic system that supports multiple vehicle subsystems such as Caution and Warning, Electrical Power Systems and Command and Data Handling (C&DH), as well as scientific payloads of varying size and complexity. The dynamic nature of the ISS configuration coupled with the increased demand for payload support places a significant burden on the inherently resource constrained computational infrastructure of the ISS. Onboard system diagnostics applications are hosted on computers that are elements of the avionics network while ground-based diagnostic applications receive only a subset of available telemetry, down-linked via S-band communications. In this paper we propose a scalable, out-of-band diagnostics architecture for ISS systems support that uses a read-only connection for C&DH data acquisition, which provides a lower cost of deployment and maintenance (versus a higher criticality readwrite connection). The diagnostics processing burden is off-loaded from the avionics network to elements of the on-board LAN that have a lower overall cost of operation and increased computational capacity. A superset of diagnostic data, richer in content than the configured telemetry, is made available to Advanced Diagnostic System (ADS) clients running on wireless handheld devices, affording the crew greater mobility for troubleshooting and providing improved insight into vehicle state. The superset of diagnostic data is made available to the ground in near real-time via an out-of band downlink, providing a high level of fidelity between vehicle state and test, training and operational facilities on the ground.
RAPID (Robot Application Programming Interface Delegate) software utilizes highly robust technology to facilitate commanding and monitoring of lunar assets. RAPID provides the ability for intercenter communication, since these assets are developed in multiple NASA centers. RAPID is targeted at the task of lunar operations; specifically, operations that deal with robotic assets, cranes, and astronaut spacesuits, often developed at different NASA centers. RAPID allows for a uniform way to command and monitor these assets. Commands can be issued to take images, and monitoring is done via telemetry data from the asset. There are two unique features to RAPID: First, it allows any operator from any NASA center to control any NASA lunar asset, regardless of location. Second, by abstracting the native language for specific assets to a common set of messages, an operator may control and monitor any NASA lunar asset by being trained only on the use of RAPID, rather than the specific asset. RAPID is easier to use and more powerful than its predecessor, the Astronaut Interface Device (AID). Utilizing the new robust middleware, DDS (Data Distribution System), developing in RAPID has increased significantly over the old middleware. The API is built upon the Java Eclipse Platform, which combined with DDS, provides platform-independent software architecture, simplifying development of RAPID components. As RAPID continues to evolve and new messages are being designed and implemented, operators for future lunar missions will have a rich environment for commanding and monitoring assets.
The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This paper describes hardware/software co-verification tools for the Xilinx Zynq-based control and data handling system that have been developed at the Jet Propulsion Laboratory (JPL) for visible-infrared imaging spectrometers. The system acquires and compresses images in real-time, in addition to programming the spectrometer (frame rate, exposure time), focus step motor, and heaters and reporting telemetry.
This paper describes a battery power model that has been developed to simulate and predict the behavior of the 50 ampere-hour nickel-cadmium battery that supports the Extreme Ultraviolet Explorer (EUVE) spacecraft in its low Earth orbit. First, for given orbit, attitude, solar array panel and spacecraft load data, the model calculates minute-by-minute values for the net power available for charging the battery for a user-specified time period (usually about two weeks). Next, the model is used to calculate minute-by-minute values for the battery voltage, current and state-of-charge for the time period. The model's calculations are explained for its three phases: sunrise charging phase, constant voltage phase, and discharge phase. A comparison of predicted model values for voltage, current and state-of-charge with telemetry data for a complete charge-discharge cycle shows good correlation. This C-based computer model will be used by the EUVE Flight Operations Team for various 'what-if' scheduling analyses.
Five accelerometers mounted near the adapter base of the Titan 3-C launch vehicle and three on the hub of the ATS-F spacecraft provided (1) data for verifying basic spacecraft mode shapes and frequencies during powered flight while attached to the launch vehicle; (2) failure mode detection and diagnostic information on in-flight anomalies; and (3) data to be used in the design of future spacecraft to be flown on the Titan 3-C. Because data from the instruments mounted on the spacecraft hub passed through an in-flight disconnect at the separation plane between the transtage and ATS-F, the moment this connector was broken, the signal to the telemetry system showed a step function change. By monitoring these telemetry traces on the ground at appropriate times during flight sequences, a positive indication of spacecraft separation was obtained. Flight data showing dynamic response at spacecraft launch vehicle interface and at the top of ATS spacecraft during significant launch events are presented in tables.
At NASA, we develop myriad Eclipse RCP applications to provide situational awareness for remote systems. The Intelligent Robotics Group at NASA Ames Research Center has developed VERVE - a high-performance, robot user interface that provides scientists, robot operators, and mission planners with powerful, interactive 3D displays of remote environments.VERVE includes a 3D Eclipse view with an embedded Java Ardor3D scenario, including SWT and mouse controls which interact with the Ardor3D camera and objects in the scene. VERVE also includes Eclipse views for exploring and editing objects in the Ardor3D scene graph, and a HUD (Heads Up Display) framework allows Growl-style notifications and other textual information to be overlayed onto the 3D scene. We use VERVE to listen to telemetry from robots and display the robots and associated scientific data along the terrain they are exploring; VERVE can be used for any interactive 3D display of data.VERVE is now open source. VERVE derives from the prior Viz system, which was developed for Mars Polar Lander (2001) and used for the Mars Exploration Rover (2003) and the Phoenix Lander (2008). It has been used for ongoing research with IRG's K10 and KRex rovers in various locations. VERVE was used on the International Space Station during two experiments in 2013 - Surface Telerobotics, in which astronauts controlled robots on Earth from the ISS, and SPHERES, where astronauts control a free flying robot on board the ISS.We will show in detail how to code with VERVE, how to interact between SWT controls to the Ardor3D scenario, and share example code.
A simplified version of the integer cosine transform (ICT) is described. For practical reasons, the transform is considered jointly with the quantization of its coefficients. It differs from conventional ICT algorithms in that the combined factors for normalization and quantization are approximated by powers of two. In conventional algorithms, the normalization/quantization stage typically requires as many integer divisions as the number of transform coefficients. By restricting the factors to powers of two, these divisions can be performed by variable shifts in the binary representation of the coefficients, with speed and cost advantages to the hardware implementation of the algorithm. The error introduced by the factor approximations is compensated for in the inverse ICT operation, executed with floating point precision. The simplified ICT algorithm has potential applications in image-compression systems with disparate cost and speed requirements in the encoder and decoder ends. For example, in deep space image telemetry, the image processors on board the spacecraft could take advantage of the simplified, faster encoding operation, which would be adjusted on the ground, with high-precision arithmetic. A dual application is found in compressed video broadcasting. Here, a fast, high-performance processor at the transmitter would precompensate for the factor approximations in the inverse ICT operation, to be performed in real time, at a large number of low-cost receivers.
Dual airborne imaging system networks were operated using a wireless line-of-sight telemetry system developed as part of a 2002 unmanned aerial vehicle (UAV) imaging mission over the USA s largest coffee plantation on the Hawaiian island of Kauai. A primary mission objective was the evaluation of commercial-off-the-shelf (COTS) 802.11b wireless technology for reduction of payload telemetry costs associated with UAV remote sensing missions. Predeployment tests with a conventional aircraft demonstrated successful wireless broadband connectivity between a rapidly moving airborne imaging local area network (LAN) and a fixed ground station LAN. Subsequently, two separate LANs with imaging payloads, packaged in exterior-mounted pressure pods attached to the underwing of NASA's Pathfinder-Plus UAV, were operated wirelessly by ground-based LANs over independent Ethernet bridges. Digital images were downlinked from the solar-powered aircraft at data rates of 2-6 megabits per second (Mbps) over a range of 6.5 9.5 km. An integrated wide area network enabled payload monitoring and control through the Internet from a range of ca. 4000 km during parts of the mission. The recent advent of 802.11g technology is expected to boost the system data rate by about a factor of five.
The X-band (8.41 GHz) frequency currently used for deep space telecommunications is too narrow (50 MHz) to support future high rate missions. Because of this NASA has decided to transition to Ka-band (32 GHz) frequencies. As weather effects cause much larger fluctuations on Ka-band than on X-band, the traditional method of using a few dBs of margin to cover these fluctuations is wasteful of power for Ka-band; therefore, a different operations concept is needed for Ka-band links. As part of the development of the operations concept for Ka-band, NASA has implemented a fully functioning Ka-band communications suite on its Mars Reconnaissance Orbiter (MRO). This suite will be used during the primary science phase to develop and refine the Ka-band operations concept for deep space missions. In order to test the functional readiness of the spacecraft and the Deep Space Network's (DSN) readiness to support the demonstration activities a series of passes over DSN 34-m Beam Waveguide (BWG) antennas were scheduled during the cruise phase of the mission. MRO was launched on August 12, 2005 from Kennedy Space Center, Cape Canaveral, Florida, USA and went into Mars Orbit on March 10, 2006. A total of ten telemetry demonstration and one high gain antenna (HGA) calibration passes were allocated to the Ka-band demonstration. Furthermore, a number of "shadow" passes were also scheduled where, during a regular MRO track over a Ka-band capable antenna, Ka-band was identically configured as the X-band and tracked by the station. In addition, nine Ka-band delta differential one way ranging ((delta)DOR) passes were scheduled. During these passes, the spacecraft and the ground system were put through their respective paces. Among the highlights of these was setting a single day record for data return from a deep space spacecraft (133 Gbits) achieved during one 10-hour pass; achieving the highest data rate ever from a planetary mission (6 Mbps) and successfully demonstrating Ka-band DDOR. In addition, DSN performed well. However, there are concerns with the active pointing of the Ka-band antennas as well as delivery of the monitor data from the stations. The spacecraft also presented challenges not normally associated with planetary missions mostly because of its very high equivalent isotropic radiated power (EIRP). This caused problems in accurately evaluating the in-flight EIRP of the spacecraft which led to difficulties evaluating the quality of the HGA calibration data. These led to the development of additional measurement techniques that could be used for future high-power deep space missions.
The Magellan spacecraft will be launched from Kennedy Space Center (KSC) within a 31-day overall launch period extending from April 28 to May 28, 1989. The launch will use the Shuttle Orbiter Atlantis to lift an Inertial Upper Stage (IUS) and the Magellan Spacecraft into low Earth orbit. After the Shuttle achieves its parking orbit, the IUS and attached Magellan spacecraft are deployed from the payload bay. After a short coast time, the two-stage IUS is fired to inject the Magellan spacecraft into an Earth-Venus transfer trajectory. The Magellan spacecraft is powered by single degree of freedom, sun-tracking, solar panels charging a set of nickel-cadmium batteries. The spacecraft is three-axis stabilized by reaction wheels using gyros and a star sensor for attitude reference. The spacecraft carries a solid rocket motor for Venus Orbit Insertion (VOI). A hydrazine propulsion system allows trajectory correction and prevents saturation of the reaction wheels. Communication with Earth through the Deep Space Network (DSN) is provided by S- and X-band telemetry channels, through alternatively a low, medium, or 3.7 m high-gain parabolic antenna rigidly attached to the spacecraft. The high-gain antenna also serves as the radar and radiometer antenna during orbit around Venus.
Prolonged longevity of cardiac implantable electronic devices (CIEDs) is needed not only as a passive response to match the prolonging life expectancy of patient recipients, but will also actively prolong their life expectancy by avoiding/deferring the risks (and costs) associated with device replacement. CIEDs are still exclusively powered by nonrechargeable primary batteries, and energy exhaustion is the dominant and an inevitable cause of device replacement. The longevity of a CIED is thus determined by the attrition rate of its finite energy reserve. The energy available from a battery depends on its capacity (total amount of electric charge), chemistry (anode, cathode, and electrolyte), and internal architecture (stacked plate, folded plate, and spiral wound). The energy uses of a CIED vary and include a background current for running electronic circuitry, periodic radiofrequency telemetry, high‐voltage capacitor reformation, constant ventricular pacing, and sporadic shocks for the cardiac resynchronization therapy defibrillators. The energy use by a CIED is primarily determined by the patient recipient's clinical needs, but the energy stored in the device battery is entirely under the manufacturer's control. A larger battery capacity generally results in a longer‐lasting device, but improved battery chemistry and architecture may allow more space‐efficient designs. Armed with the necessary technical knowledge, healthcare professionals and purchasers will be empowered to make judicious selection on device models and maximize the utilization of all their energy‐saving features, to prolong device longevity for the benefits of their patients and healthcare systems.
The Perseverance rover represents NASA’s latest achievement in Mars exploration. Landing successfully on 18 Feb 2021, the rover’s transmitted data during its entry, descent, and landing (EDL) were captured by the Mars Reconnaissance Orbiter (MRO) and the Mars Atmosphere and Volatile Evolution (MAVEN) orbiter. This data, broadcast in near-realtime to the world, allowed everyone to share in the excitement (and “terror”) of the day. The images returned thereafter included the first images of the new landing site, video of the landing itself taken from a variety of vantage points, and eventually the historic images of the first powered flight on another planet. Behind the scenes, the return of that data to Earth was accomplished via Mars orbiters operated by NASA and ESA, using three different ground tracking networks. Considered together, this Mars Relay Network (MRN) enabled the successful, timely, and unobtrusive return of the rover’s data. This paper describes the preparations taken by the participants of the MRN in anticipation of the arrival of Perseverance at Mars. These were not only focused on successfully acquiring the rover’s critical event telemetry during its EDL, but also on readying the network to return the rover’s data on an ongoing basis as it pursued its mission objectives. Included is a brief description of the MRN, which represents a highly successful international collaboration and continues as critical infrastructure for NASA’s and ESA’s ongoing Mars exploration. Also summarized are the activities performed prior to EDL, including landing site reconnaissance and mission test and training activities; those activities performed on EDL day, especially the recording, return, and processing of the rover’s critical event telemetry; and those activities that are now being performed on an ongoing basis during the rover’s surface operations, including an outline of the planning processes that enable relay services. Finally, a description of the performance of the network to-date on behalf of the Perseverance rover is given, summarizing the success of the network to provide support to both it and other spacecraft on the surface of Mars.