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The objectives are to examine recent trends in the reduction of size, weight, and power (SWaP) requirements of sensor systems for environmental perception and to explore new technology that may overcome limitations in current systems. Improving perception systems to facilitate situation awareness is critical in the move to introduce increasing autonomy in aerial systems. Whether the autonomy is in the current state-of-the-art of increasing automation or is enabling cognitive decisions that facilitate adaptive behavior, collection of environmental information and fusion of that information into knowledge that can direct actuation is imperative to decisions resulting in appropriate behavior. Artificial sensory systems such as cameras, radar, LIDAR, and acoustic sensors have been in use on aircraft for many years but, due to the large size and weight of the airplane and electrical power made available through powerful engines, the SWaP requirements of these sensors was inconsequential. With the proliferation of Remote Piloted Vehicles (RPV), the trend is in significant reduction in SWaP of the vehicles. This requires at least an equivalent reduction in SWaP for the sensory systems. A survey of some currently available sensor systems and changing technology will reveal the trend toward reduction of SWaP of these systems and will predict future reductions. A new technology will be introduced that provides an example of a desirable new trend. A new device replaces multiple conventional sensory devices facilitating synchronization, localization, altimetry, collision avoidance, terrain mapping, and data communication in a single integrated, small form-factor, extremely lightweight, and low power device that it is practical for integration into small autonomous vehicles and can facilitate cooperative behavior. The technology is based on Ultra WideBand (UWB) radio using short pulses of energy rather than continuous sine waves. The characteristics of UWB yield several desirable characteristics to facilitate integration of perception for autonomous activities. The capabilities of this device and its limitations will be assessed.
The design of a sensor fault tolerant system which uses analytical redundancy for the Terminal Configured Vehicle (TCV) research aircraft in a Microwave Landing System (MLS) environment was studied. The fault tolerant system provides reliable estimates for aircraft position, velocity, and attitude in the presence of possible failures in navigation aid instruments and onboard sensors. The estimates, provided by the fault tolerant system, are used by the automated guidance and control system to land the aircraft along a prescribed path. Sensor failures are identified by utilizing the analytic relationship between the various sensor outputs arising from the aircraft equations of motion.
In a continuing program of research and development, a system has been demonstrated that makes high-speed measurements of thermal infrared radiance from gas-turbine engine exhaust streams. When a gas-turbine engine is operated under conditions that minimize the emission of pollutants, there is a risk of crossing the boundary from stable to unstable combustion. Combustion instability can lead to engine damage and even catastrophic failure. Sensor systems of the type under development could provide valuable data during the development testing of gas-turbine engines or of engine components. A system of the type under development makes high-speed measurements of thermal infrared radiance from the engine exhaust stream. The sensors of this system can be mounted outside the engine, which eliminates the need for engine case penetrations typical with other engine dynamics monitors. This is an important advantage in that turbine-engine manufacturers consider such penetrations to be very undesirable. A prototype infrared sensor system has been built and demonstrated on a turbine engine. This system includes rugged and inexpensive near-infrared sensors and filters that select wavelengths of infrared radiation for high sensitivity. In experiments, low-frequency signatures were consistently observed in the detector outputs. Under some conditions, the signatures also included frequency components having one or two radiance cycles per engine revolution. Although it has yet to be verified, it is thought that the low-frequency signatures may be associated with bulk-mode combustion instabilities or flow instabilities in the compressor section of the engine, while the engine- revolution-related signatures may be indicative of mechanical problems in the engine. The system also demonstrated the ability to detect transient high-radiance events. These events indicate hot spots in the exhaust stream and were found to increase in frequency during engine acceleration.
The Sensor Data Qualification System (SDQS) is being developed to provide a sensor fault detection capability for NASA s next-generation launch vehicles. In addition to traditional data qualification techniques (such as limit checks, rate-of-change checks and hardware redundancy checks), SDQS can provide augmented capability through additional techniques that exploit analytical redundancy relationships to enable faster and more sensitive sensor fault detection. This paper documents the results of a study that was conducted to determine the best approach for implementing a SDQS network configuration that spans multiple subsystems, similar to those that may be implemented on future vehicles. The best approach is defined as one that most minimizes computational resource requirements without impacting the detection of sensor failures.
The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.
The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.
A three axis fluidic airspeed sensor system has been fabricated and wind tunnel tested. The complete system consists of the fluidic sensor, air power supply and instrumentation and readout. The system is adapted to aircraft and requires only the standard aircraft 28V dc supply to function.
The interactive information processing for the mesoscale analysis and space sensor (MASS) program is reported. The development and implementation of new spaceborne remote sensing technology to observe and measure atmospheric processes is described. The space measurements and conventional observational data are processed together to gain an improved understanding of the mesoscale structure and dynamical evolution of the atmosphere relative to cloud development and precipitation processes. A Research Computer System consisting of three primary computers was developed (HP-1000F, Perkin-Elmer 3250, and Harris/6) which provides a wide range of capabilities for processing and displaying interactively large volumes of remote sensing data. The development of a MASS data base management and analysis system on the HP-1000F computer and extending these capabilities by integration with the Perkin-Elmer and Harris/6 computers using the MSFC's Apple III microcomputer workstations is described. The objectives are: to design hardware enhancements for computer integration and to provide data conversion and transfer between machines.
We examine the requirements for on-board aircraft sensor systems that would allow pilots to 'see through' poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution. We recommend using both millimeter-wave and infrared sensor systems, blending the images using multiresolution digital-image pyramid-processing technology, and fusing the resulting real-time images with stored database imagery of the same scene.
CASES (Controls, Astrophysics and Structures Experiment in Space) is a proposed space experiment to collect x-ray images of the galactic center and solar disk with unprecedented resolution. This requires precision pointing and suppression of vibrations in the long flexible structure that comprises the 32-m x-ray telescope optical bench. Two separate electro-optical sensor systems are provided for the ground test facility (GTF). The Boom Motion Tracker (BMT) measures eigenvector data for post-mission use in system identification. The Tip Displacement Sensor (TDS) measures boom tip position and is used as feedback for the closed-loop control system that stabilizes the boom. Both the BMT and the TDS have met acceptance specifications and were delivered to MSFC in February 1992. This paper describes the sensor concept, the sensor configuration as implemented in the GTF, and the results of characterization and performance testing.
A surface-launched acoustic wave sensor tag system for remotely sensing and/or providing identification information using sets of surface acoustic wave (SAW) sensor tag devices is characterized by acoustic wave device embodiments that include coding and other diversity techniques to produce groups of sensors that interact minimally, reducing or alleviating code collision problems typical of prior art coded SAW sensors and tags, and specific device embodiments of said coded SAW sensor tags and systems. These sensor/tag devices operate in a system which consists of one or more uniquely identifiable sensor/tag devices and a wireless interrogator. The sensor device incorporates an antenna for receiving incident RF energy and re-radiating the tag identification information and the sensor measured parameter(s). Since there is no power source in or connected to the sensor, it is a passive sensor. The device is wirelessly interrogated by the interrogator.
A surface-launched acoustic wave sensor tag system for remotely sensing and/or providing identification information using sets of surface acoustic wave (SAW) sensor tag devices is characterized by acoustic wave device embodiments that include coding and other diversity techniques to produce groups of sensors that interact minimally, reducing or alleviating code collision problems typical of prior art coded SAW sensors and tags, and specific device embodiments of said coded SAW sensor tags and systems. These sensor/tag devices operate in a system which consists of one or more uniquely identifiable sensor/tag devices and a wireless interrogator. The sensor device incorporates an antenna for receiving incident RF energy and re-radiating the tag identification information and the sensor measured parameter(s). Since there is no power source in or connected to the sensor, it is a passive sensor. The device is wirelessly interrogated by the interrogator.
A fiber-optic sensor system is designed to measure magnetic fields associated with a lightning stroke. Field vector magnitudes are detected and processed for multiple locations. Since physical limitations prevent the sensor elements from being located in close proximity to highly conductive materials such as aluminum, the copper wire sensor elements (3) are located inside a 4-cubic-in. (.66-cubic-cm) plastic housing sensor head and connected to a fiber-optic conversion module by shielded cabling, which is limited to the shortest length feasible. The signal path between the conversion module and the avionics unit which processes the signals are fiber optic, providing enhanced immunity from electromagnetic radiation incident in the vicinity of the measurements. The sensors are passive, lightweight, and much smaller than commercial B-dot sensors in the configuration which measures a three-dimensional magnetic field. The system is expandable, and provides a standard-format output signal for downstream processing. Inside of the sensor head, three small search coils, each having a few turns on a circular form, are mounted orthogonally inside the non-metallic housing. The fiber-optic conversion module comprises three interferometers, one for each search coil. Each interferometer has a high bandwidth optical phase modulator that impresses the signal received from its search coil onto its output. The output of each interferometer travels by fiber optic cable to the avionics unit, and the search coil signal is recovered by an optical phase demodulator. The output of each demodulator is fed to an analog-to-digital converter, whose sampling rate is determined by the maximum expected rate of rise and peak signal magnitude. The output of the digital processor is a faithful reproduction of the coil response to the incident magnetic field. This information is provided in a standard output format on a 50-ohm port that can be connected to any number of data collection and processing instruments and/or systems. The measurement of magnetic fields using fiber-optic signal processing is novel because it eliminates limitations of a traditional B-dot system. These limitations include the distance from the sensor to the measurement device, the potential for the signal to degrade or be corrupted by EMI from lightning, and the size and weight of the sensor and associated plate.
Various design configurations used for testing IR fiber-optic (IFO) fire-sensor concepts are presented. Responsibility measurements conducted to select the best concept are reviewed. The results indicate that IFO fire-sensor systems based on distributed fiber sensors are feasible for future aerospace applications. For Space Station Freedom, these systems offer alternative fire detectors for monitoring areas within equipment or stage compartments where the ventilation may be inadequate for proper operation of smoke detectors. They also allow a large number of areas to be monitored by a single central detector unit, which reduces the associated cost and weight.
Combustion systems make up a large sum of the world’s yearly energy production despite advances in renewable energy sources. Precise control of pressure and temperature in combustion chambers allows for lower carbon emissions, and overall higher efficiency. Wireless temperature and pressure sensors are critical for the operation of combustion chambers. Energy harvesters have emerged as a viable way to power wireless sensors when heat and mechanical energy are available. Lithium niobate (LNB), barium titanate (BTO), and lead zirconate titanate (PZT) pyroelectric ceramics were studied and fabricated through additive manufacturing (AM) for use as energy harvesting structures in combustion environments. The electric power generation potential of LNB and PZT ceramics was studied by varying the temperature from 50 to 60 °C and by introducing cyclic compression loads of 2000 N amplitude. It was found that thermal energy conversion had the highest output of 500 nW and that combined thermal and mechanical conversion did not increase the harvesting potential because of the competing contributions of both effects. Powder bed and slurry extrusion AM methods were used to fabricate BTO and PZT ceramic structures. Optimization of the powder-based binder jetting method produced BTO ceramics with a relative density of 36.77% a piezoelectric coefficient of 153 pC/N. The density of the ceramics increased up to 56% when increasing the saturation of binder in the powder to because of liquid phase sintering. Finally, PZT structures were manufactured through AM and fin features were added to the design to enhance the heat transfer along the material. The harvested power density of the flat samples was 3.643 μW/cm 3 and of the finned samples was 3.034 μW/cm3. This research paves the ways for the development of self-powered wireless sensors in critical areas of operation such as combustion.
A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.