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This paper features a set of advanced technologies for autonomy and intelligence in advanced inspection systems of facility operations. These technologies offer a significant contribution to set a path to establish a system and an operating environment with autonomy and intelligence for inspection, monitoring and safety via gas and ambient sensors, video mining and speech recognition commands on unmanned ground vehicles and other platforms to support operational activities in the Cryogenics Test bed and other facilities and vehicles. These advanced technologies are in current development and progress and their functions and operations require guidance and formulation in conjunction with the development team(s) toward the system architecture.

Simultaneous crank-angle-resolved measurements of gasoline vapor concentration, gas temperature, and liquid fuel droplet scattering were made with three-color infrared absorption in a direct-injection spark-ignition engine with premium gasoline. The infrared light was coupled into and out of the cylinder using fiber optics incorporated into a modified spark plug, allowing measurement at a location adjacent to the spark plug electrode. Two mid-infrared (mid-IR) laser wavelengths were simultaneously produced by difference-frequency-generation in periodically poled lithium niobate (PPLN) using one signal and two pump lasers operating in the near-infrared (near-IR). A portion of the near-IR signal laser residual provided a simultaneous third, non-resonant, wavelength for liquid droplet detection. This non-resonant signal was used to subtract the influence of droplet scattering from the resonant mid-IR signals to obtain vapor absorption signals in the presence of droplet extinction.

Remote Tower Sensor Systems are proof-of-concept prototypes being developed by NASA/Ames Research Center (NASA/ARC) with collaboration with the FAA and NOAA. RTSS began with the deployment of an Airport Approach Zone Camera System that includes real-time weather observations at San Francisco International Airport. The goal of this research is to develop, deploy, and demonstrate remotely operated cameras and sensors at several major airport hubs and un-towered airports. RTSS can provide real-time weather observations of airport approach zone. RTSS will integrate and test airport sensor packages that will allow remote access to real-time airport conditions and aircraft status.

Biomolecules exhibit specific binding and high affinity for their ligands. These properties can be exploited to produce sensitive, specific, real-time sensors for analytes that cannot be readily monitored by other methods. Several technologies for environmental monitoring using proteins are currently being developed. We discuss specific challenges to practical application of a family of protein-based sensors derived from bacterial periplasmic binding proteins. We also present recent work to address these challenges.

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.

Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

During 1995, we tested instruments and attempted a seed-to-seed experiment with Super-Dwarf wheat in the Russian Space Station Mir. Utah instrumentation included four IR gas analyzers (CO2 and H2O vapor, calculate photosynthesis, respiration, and transpiration) and sensors for air and leaf (IR) temperatures, O2, pressure, and substrate moisture (16 probes). Shortly after planting on August 14, three of six fluorescent lamp sets failed; another failed later. Plastic bags, necessary to measure gas exchange, were removed. Hence, gases were measured only in the cabin atmosphere. Other failures led to manual watering, control of lights, and data transmission. The 57 plants were sampled five times plus final harvest at 90 d. Samples and some equipment (including hard drives) were returned to earth on STS-74 (Nov. 20). Plants were disoriented and completely vegetative. Maintaining substrate moisture was challenging, but the moisture probes functioned well.

This paper describes a multi-disciplinary damage detection methodology that can aid in detecting and diagnosing a damage in a given structural system, not limited to the example of a rotating gear presented here. Damage detection is performed on the gear stress data corresponding to the steady state conditions. The normal and damage data are generated by a finite-difference solution of elastodynamic equations of velocity and stress in generalized coordinates1. The elastodynamic solution provides a knowledge of the stress distribution over the gear such as locations of stress extrema, which in turn can lead to an optimal placement of appropriate sensors over the gear to detect a potential damage. The damage detection is performed by a multi-function optimization that incorporates Tikhonov kernel regularization reinforced by an added Laplacian regularization term as used in semi-supervised machine learning. Damage is mimicked by reducing the rigidity of one of the gear teeth.

This paper discussed how data mining techniques could give advantage to the robot in navigation, in terms of speed. The input of our navigation system is the sensory information collected by the robot's equipped landmark sensor and infra-red sensor, the process of the system is the proposed data mining technique, and the output of the system is the execution of the moving direction in a 2D Martian environment. The results demonstrate efficient goal-oriented navigation using data mining techniques.

Several recent papers describe closed loop fuel-air ratio control systems designed to operate at stoichiometric conditions because of the high three-way catalyst conversion efficiencies which occur only in a narrow band around stoichiometric. This paper investigates closed loop control of fuel-air ratio using a temperature compensated zirconia sensor at other than stoichiometric conditions. If engines can be made to run at very lean(Φ≈0.6-0.7) equivalence ratios through greater attention to proper fuel-air mixing and vaporization, CO, HC, and NOx emissions are minimized simultaneously. Closed loop control in the lean region makes the system insensitive to parameter variations and allows the fuel-air ratio to be maintained closer to the lean limit than would be possible under conventional open loop conditions.

Accurate root zone moisture control in microgravity plant growth systems is problematic. With gravity, excess water drains along a vertical gradient, and water recovery is easily accomplished. In microgravity, the distribution of water is less predictable and can easily lead to flooding, as well as anoxia. Microgravity water delivery systems range from solidified agar, water-saturated foams, soils and hydroponics soil surrogates including matrix-free porous tube delivery systems. Surface tension and wetting along the root substrate provides the means for adequate and uniform water distribution. Reliable active soil moisture sensors for an automated microgravity water delivery system currently do not exist. Surrogate parameters such as water delivery pressure have been less successful.

This paper presents a new measurement technique for in-cylinder gas temperature and residual gas concentration during the compression stroke of an internal combustion (IC) engine. This technique is based on the infrared absorption of water vapor by a wavelength modulated laser. Wavelength modulation spectroscopy with second harmonic detection (WMS-2f) was adopted to enable the short-path measurements over a wide range of temperatures and pressures corresponding to the late compression stroke in a typical automotive engine. The WMS-2f signal is detected through a bandpass filter at a width of 7.5 kHz, enabling crank angle-resolved measurements. The temperature is determined from the ratio of optical absorption for two overtone transitions of water vapor in the intake gas mixture, and the H2O concentration is determined from this inferred temperature and the absorption for one of the transitions.