Showing papers presented at "IEEE Aerospace Conference in 2004"

A trust model based routing protocol for secure ad hoc networks

Abstract: Security issues have been emphasized when mobile ad hoc networks (MANETs) are employed into military and aerospace fields. We design a novel secure routing protocol for MANETs. This protocol TAODV (Trusted AODV) extends the widely used AODV (ad hoc on-demand distance vector) routing protocol and employs the idea of a trust model to protect routing behaviors in the network layer of MANETs. In the TAODV, trust among nodes is represented by opinion, which is an item derived from subjective logic. The opinions are dynamic and updated frequently as our protocol specification: if one node performs normal communications, its opinion from other nodes' points of view can be increased; otherwise, if one node performs some malicious behaviors, it is ultimately denied by the whole network. A trust recommendation mechanism is also designed to exchange trust information among nodes. The salient feature of TAODV is that, using trust relationships among nodes, there is no need for a node to request and verify certificates all the time. This greatly reduces the computation overheads. Meanwhile, with neighbors' trust recommendations, a node can make objective judgement about another node's trustworthiness to maintain the whole system at a certain security level.

A model-based approach to prognostics and health management for flight control actuators

Abstract: Impact technologies have developed a robust modeling paradigm for actuator fault detection and failure prediction. This model-based approach to prognostics and health management (PHM) applies physical modeling and advanced parametric identification techniques, along with fault detection and failure prediction algorithms, in order to predict the time-to-failure for each of the critical, competitive failure modes within the system. Advanced probabilistic fusion strategies are also leveraged to combine both collaborative and competitive sources of evidence, thus producing more reliable health state information. These algorithms operate only on flight control command/response data. This approach for condition-based maintenance provides reliable early detection of developing faults. As an advantage over 'black-box' health-monitoring schemes, faults and failure modes are traced back to physically meaningful system parameters, providing the maintainer with invaluable diagnostic and prognostic information. The developed model-based reasoner was validated and demonstrated on an electromechanical actuator (EMA) provided by Moog, Inc.

Vision-based road-following using a small autonomous aircraft

Abstract: This paper describes the vision-based control of a small autonomous aircraft following a road. The computer vision system detects natural features of the scene and tracks the roadway in order to determine relative yaw and lateral displacement between the aircraft and the road. Using only the vision measurements and onboard inertial sensors, a control strategy stabilizes the aircraft and follows the road. The road detection and aircraft control strategies have been verified by hardware in the loop (HIL) simulations over long stretches (several kilometers) of straight roads and in conditions of up to 5 m/s of prevailing wind. Hardware experiments have also been conducted using a modified radio-controlled aircraft. Successful road following was demonstrated over an airfield runway under variable lighting and wind conditions. The development of vision-based control strategies for unmanned aerial vehicles (UAVs), such as the ones presented here, enables complex autonomous missions in environments where typical navigation sensor like GPS are unavailable.

Data-driven neural network methodology to remaining life predictions for aircraft actuator components

Abstract: Actuators are complex electro-hydraulic or mechanical mechanisms utilized in aircraft to drive flight control surfaces, landing gear, cargo doors, and weapon systems. Impact has developed a prognostic and health management (PHM) methodology for these critical systems that includes signal processing and neural network tracking techniques, along with automated reasoning, classification, knowledge fusion, and probabilistic failure mode progression algorithms. The processing utilizes the command/response signal and hydraulic pressure data from the actuators and provides a real-time assessment of the current/future actuator health state. This methodology was applied to F/A-18 stabilator electro-hydraulic servo valves (EHSVs) using test stand data provided by Boeing Phantom works. The automated module demonstrated excellent health state classification results. The prognosis was also successfully performed however no data was available to validate the prediction. These algorithms were developed with consideration to sensor/processing limitations for potential onboard implementation. Many of the PHM elements presented here could also be adapted for other actuator types and applications.

Path following using visual odometry for a Mars rover in high-slip environments

Abstract: A system for autonomous operation of Mars rovers in high slip environments has been designed, implemented, and tested. This system is composed of several key technologies that enable the rover to accurately follow a designated path, compensate for slippage, and reach intended goals independent of the terrain over which it is traversing (within the mechanical constraints of the mobility system). These technologies include: visual odometry, full vehicle kinematics, a Kalman filter pose estimator, and a slip compensation/path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs using a maximum likelihood motion estimation algorithm. The full vehicle kinematics for a rocker-bogie suspension system estimates motion, with a no-slip assumption, by measuring wheel rates, and rocker, bogie, and steering angles. The Kalman filter merges data from an inertial measurement unit (IMU) and visual odometry. This merged estimate is then compared to the kinematic estimate to determine (taking into account estimate uncertainties) if and how much slippage has occurred. If no statistically significant slippage has occurred then the kinematic estimate is used to complement the Kalman filter estimate. If slippage has occurred then a slip vector is calculated by differencing the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the necessary wheel velocities and steering angles to compensate for slip and follow the desired path.

Silicon-carbide (SiC) semiconductor power electronics for extreme high-temperature environments

Abstract: This paper discusses the current state of SiC electronics research at Arkansas Power Electronics International, Inc. (APEI) with regard to high-temperature environments and applications. The University of Arkansas (UA) researchers' modeling and characterization of SiC power devices for these high-temperature environments are also discussed. Devices to be covered include SiC Schottky diodes, SiC power MOSFETs, and SiC static-induction-transistors (SITs). The paper reviews the current application of these devices to the specific harsh environments of deep Earth drilling and combat electric vehicles, as well as outline APEI's research work into developing operational SiC motor drives for these systems. It is proposed that this technology development be transferred to NASA space exploration applications. Two areas within the NASA program that would find this technology highly beneficial are (1) probes and landers that must operate in high-temperature environments and (2) ultra-lightweight power electronics for satellite and spacecraft power converter systems.

Similarity based modeling of time synchronous averaged vibration signals for machinery health monitoring

Abstract: Monitoring rotating machinery is often accomplished with the aid of vibration sensors. The vibration sensor signals contain a wealth of complex information that characterizes the dynamic behavior of the machinery. Transforming this information into useful knowledge about the health of the machine can be challenging due to the presence of extraneous noise sources and variations in the vibration signal itself. This is particularly true in situations in which the rotating machinery is monitored under varying loads and/or speeds. In order for any gained knowledge or insight into the health of machinery to be useful, it must be actionable. This is achieved by detecting incipient faults as early as possible. A novel approach to vibration monitoring that employs a multivariate similarity-based modeling (SBM) technique to characterize the expected behavior of time synchronous averaged spectral features is shown to enable the detection in rotating machinery. This in turn facilitates the assessment of machine health and enables fault diagnostics and ultimately prognostics. SBM has been applied successfully to a variety of non-vibration related multi-sensor, health monitoring applications. Our new approach builds off of these experiences and a combination of signal processing algorithms to expand the overall applicability of SBM into single sensor vibration monitoring. We discuss an approach to gearbox fault monitoring using vibration data and SBM. This new approach is described in detail and is applied to actual H-60 gearbox vibration data acquired from seeded fault tests conducted by U.S. Naval Air Systems Command (NAVAIR) at the Helicopter Transmission Test Facility (HTTF) in Patuxent River, MD in 2001 and 2002.

PHM a key enabler for the JSF autonomic logistics support concept

Abstract: A discussion of the Joint Strike Fighter's PHM system and its relationship to the far-reaching autonomic logistics (AL) support concept is presented in this paper. By design, PHM is one of the key enabler for this new and revolutionary AL support concept. Overall PHM architecture is described with emphasis on its capabilities and its aims to enhance aircraft safety; improve sortie generation rate; decrease logistics footprint; and significant reduce operation and support costs. The key elements of the AL concept are presented. Program background, user "needs", and potential benefits are explored; and related to show how the PHM and AutoLog visions evolved to their current concept and status.

Real-time fault detection and situational awareness for rovers: report on the Mars technology program task

Abstract: In this paper we describe the results of a project funded by the Mars technology program at NASA, aimed at developing algorithms to meet this requirement. We describe a number of particle filtering-based algorithms for state estimation which we have demonstrated successfully on diagnosis problems including the K-9 rover at NASA Ames Research Center and the Hyperion rover at CMU. Due to the close interaction between a rover and its environment, traditional discrete approaches to diagnosis are impractical for this domain. Therefore we model rover subsystems as hybrid discrete/continuous systems. There are three major challenges to make particle filters work in this domain. The first is that fault states typically have a very low probability of occurring, so there is a risk that no samples enter fault states. The second issue is coping with the high-dimensional continuous state spaces of the hybrid system models, and the third is the severely constrained computational power available on the rover. This means that very few samples can be used if we wish to track the system state in real time. We describe a number of approaches to rover diagnosis specifically designed to address these challenges.

Joint subspace detection of hyperspectral targets

Abstract: Joint subspace detection (JSD) arises from a Bayesian formulation of the binary detection problem, as contrasted with the "fixed but unknown parameter" approach that generates the generalized likelihood ratio (GLR) test. The Bayesian philosophy allows the incorporation of prior knowledge gleaned from empirical experience into the design of a detection algorithm. The knowledge appears in the form of probability distributions for parameters considered deterministic in the GLR method. An example of this principle, called complementary subspace detection, has been applied to hyperspectral data and, with appropriate subspace selection, is shown to outperform the traditional detection techniques over a wide range of assumed prior knowledge of target distribution.

The fundamentals of designing deployable structures with elastic memory composites

Abstract: Elastic memory composite (EMC) materials exhibit many favorable qualities for deployable structures and have piqued a broad interest within America's deployable space structures industry. EMC materials are similar to traditional fiber-reinforced composites except for the use of a thermoset shape memory resin that enables much higher packaging strains than traditional composites without damage to the fibers or the resin. This unique capability is being exploited in the development of very efficient EMC structural components for deployable spacecraft systems. The present paper is intended primarily to help deployable system designers develop a better understanding of the special capabilities of EMC materials, and the unique considerations that must be applied when engineering structural components with these materials. Specifically, the paper discusses: 1) the impacts of incorporating EMC materials on deployable system design, 2) analyses for packaging strain, deployment time, and deployment energy; and 3) requirements and concepts for heating systems.

Multi-mission radioisotope thermoelectric generator (MMRTG) program overview

Abstract: Future NASA missions require safe, reliable, long-lived power systems for surface exploration of planetary bodies such as Mars as well as exploration of the solar system in the vacuum of space beyond Earth orbit. To address this need, the Department of Energy and NASA have initiated the development of radioisotope power systems, including the Multi-Mission Radioisotope Thermoelectric Generator (MMRTG). In June of 2003, the Department of Energy (DOE) awarded the MMRTG system design, development, test and integration contract to a team led by the Boeing Company's Rocketdyne Propulsion and Power Division. Boeing and Teledyne Energy Systems collaborated on an MMRTG design concept based on heritage, SNAP 19, thermoelectric converter design utilized by Teledyne for previous space exploration missions. Boeing subsequently awarded a major subcontract to Teledyne Energy Systems to design and produce the thermoelectric converter system for the MMRTG. The MMRTG is designed to operate on planetary bodies as well as in the vacuum of space. At beginning of mission, the MMRTG is designed to generate a minimum of 110 Watts of power at 28 volts DC, and to have a design life of at least 14 years. The power level was selected to afford the capabilities of meeting the potential needs of a wider variety of planetary lander and deep space missions. Potential mission concepts that could benefit from use of the MMRTG include a Titan Biological Explorer - with both a balloon mission and a rover mission, the Mars Science Laboratory (MSL), with a follow-on Astrobiology Field Laboratory mission and finally a Neptune/Triton Orbiter mission.

Recent developments in the ROAMS planetary rover simulation environment

Abstract: This paper describes recent developments in the ROAMS physics-based simulator for planetary surface exploration rover vehicles. ROAMS includes models for various subsystems and components of the vehicle including its mechanical subsystem, sensors, on-board resources, on-board control software, the terrain environment and terrain/vehicle interactions. The ROAMS simulator can be used in stand-alone mode, for closed-loop simulation with on-board software or for operator-in-the-loop simulations.

Trade space exploration of satellite datasets using a design by shopping paradigm

Abstract: One of the goals of early stage conceptual design is to execute broad trade studies of possible design concepts, evaluating them for their capability to meet minimum requirements, and choosing the one that best satisfies the goals of the project. To support trade space exploration, we have developed the advanced trade space visualizer (ATSV) that facilitates a design by shopping paradigm, which allows a decision-maker to form a preference a posteriori and use this preference to select a preferred satellite. Design automation has allowed us to implement this paradigm, since a large number of designs can be synthesized in a short period of time. The ATSV uses multidimensional visualization techniques, preference shading, and Pareto frontier display to visualize satellite trade spaces.

NASA/JPL Tumbleweed polar rover

Abstract: The Tumbleweed rover, currently under development at the Jet Propulsion Laboratory (JPL) in Pasadena, California, is a large, windblown, inflated ball, which carries an instrument payload in its interior. Such rovers offer an effective and simple means of gathering data over large spatial extents of Earth, Mars, and other solar system bodies. Tumbleweeds could prove to be a safe and economical way of deploying instruments such as a ground penetrating radar or a magnetometer in numerous hostile environments. The latest version of the rover was recently deployed in Greenland, where it completed a more than 130km autonomous traverse across an ice sheet. Communicating via the Iridium satellite network, the rover in question successfully and reliably relayed live GPS, temperature, and pressure data to a ground station at JPL for nearly ten days. The follow-on rover is currently being readied for a traverse from the South Pole to the coast of Antarctica some 2000km away. The Antarctic test is set to take place in February of 2004 and will serve to verify Tumbleweed as an effective means of harvesting data in extreme and remote settings.

A review of technology developments in flywheel attitude control and energy transmission systems

Abstract: In the past decade there has been an upswing in the interest of flywheel energy storage systems for space applications. This interest has been driven by limitations of chemical batteries for Air Force mission concepts, advances in microprocessors and composite materials, and the promise of using flywheel systems for energy storage and as attitude control actuators. The primary issues are power efficiency, mass and size, and long-term stability. Flywheels as one-to-one replacements for spacecraft batteries are competitive for only a few special missions. When flywheels replace components in two major bus subsystems, the potential weight and volume benefits are attractive. The objective of this paper is to describe the progression of flywheel technology state-of-the-art for integrated power and attitude control (IPAC) systems in space applications, and describe current AFRL efforts. The main technology areas that are addressed in this paper are flywheel designs, bearings containment and safety, and combined power distribution and attitude control.

Visual, tactile, and vibration-based terrain analysis for planetary rovers

Abstract: Future planetary exploration missions can require rovers to perform difficult tasks in rough terrain, with limited human supervision. Knowledge of terrain physical characteristics would allow a rover to adapt its control and planning strategies to maximize its effectiveness. This paper describes recent and current work at MIT in the area of onboard terrain estimation and sensing utilizing visual, tactile, and vibrational feedback. A vision-based method for measuring wheel sinkage is described. A tactile method for on-line terrain parameter estimation is also presented. Finally, a method for terrain classification based on analysis of vibration in the rover suspension is described. It is shown through simulation and experimental results that these methods can lead to accurate and efficient understanding of a rover's physical surroundings.

Prognostic and health management for avionics

Abstract: This paper describes methodologies and tools to anticipate in real-time, the onset of failures in electronic equipment. Currently developed techniques for prognostics and health management (PHM), depend on the observation of precursor variables and an imputation from them of impending failure. In electronic systems, such variables are difficult, impossible or expensive to obtain, so we propose a model-based technique utilizing embedded life models and environmental information obtained from aircraft mounted sensors that measure those parameters that most significantly accelerate failure in electronics, i.e. temperature, temperature variation, vibration and shock. This technology is referred to throughout this paper as electronics prognostics and health management (ePHM).

Detecting, tracking, and counteracting terrorist networks via hidden Markov models

Abstract: In reaction to the tragic events of September 11th 2001, DARPA made plans to develop a terrorism information awareness system with an eye to the detection and interdiction of terrorist activities. Under this program and in conjunction with Aptima, Inc., the University of Connecticut is developing its adaptive safety analysis and monitoring (ASAM) tool for assisting US intelligence analysts with: 1) identifying terrorist threats; 2) predicting possible terrorist actions; and 3) elucidating ways to counteract terrorist activities. The focus of this paper, and an important part of the ASAM tool, is modeling and detecting terrorist networks using hidden Markov models (HMMs). The HMMs used in the ASAM tool model the time evolution of suspicious patterns within the information space gathered from sources such as financial institutions, intelligence reports, newspapers, emails, etc. Here we report our software's ability to detect multiple terrorist networks within the same observation space, distinguish transaction "signatures" of terrorist activity from the ambient background of transactions of benign origin, and incorporate information relating to terrorist activity, timing and sequence.

The SPHERES Guest Scientist Program: collaborative science on the ISS

Abstract: The SPHERES Guest Scientist Program (GSP) supports the efforts of geographically distributed researchers at MIT, the U.S. Department of Defense, NASA, and elsewhere, in the development of algorithms for the SPHERES formation-flying and docking testbed. The GSP consists of a test development framework, a robust and flexible interface to the SPHERES flight software, a portable high-fidelity simulation, two laboratory testbeds, and data analysis utilities. The SPHERES testbed will be operated in bi-weekly test sessions on-board the International Space Station. Updates to the flight software can be uploaded immediately prior to each test session, allowing guest scientists the opportunity to revise and improve their algorithms from one session to the next. The SPHERES flight software architecture and the GSP interface design contribute to the flexibility of the testbed, and minimize nonproductive labor by simplifying algorithm implementation.

The formation control testbed

Abstract: Terrestrial planet finder (TPF) is a space telescope mission which performs spectral analysis of the infrared emissions from extrasolar planets, and which searches for carbon-based life on such planets. One configuration being considered for this mission is a stellar interferometer with several collectors and a combiner on separate spacecraft flying in a tightly controlled formation. The distance to earth for this mission are sufficiently great that having ground in the loop for reconfiguration or collision avoidance maneuvers impractical. Moreover, because of constraints in the orientation of the spacecraft relative to the sun, limitations on the field of view of relative range and bearing sensors, and restrictions on the orientations of thrusters, both the attitude and the relative position of each spacecraft in the formation must be taken into account in the event of a temporary sensing or control fault during maneuvers. These maneuvers include initial deployment of the formation, reconfiguration, and collision avoidance maneuvers. The formation algorithms and simulation testbed (FAST) and the formation control testbed (FCT) at JPL are being built to simulate and demonstrate 6 degree of freedom, autonomous formation flying and reconfiguration for TPF. The testbeds are complementary. Control algorithms simulated in the FAST are tested in the FCT in order to validate the FAST. This paper describes the design and construction of the formation control testbed. The FCT consists of three robots navigating on an air bearing floor, propelled by cold gas thrusters. Each robot contains an attitude platform supported on a spherical air bearing which provides three rotational degrees of freedom. The sixth degree of freedom, vertical translation, is provided by a powered vertical stage, actively controlled to provide a simulated zero-g environment for the attitude platform.

Life consumption monitoring for electronics prognostics

Abstract: Life consumption monitoring is a prognostic method to assess the remaining life of a product in its actual life-cycle environment by continuously or periodically measuring the product's performance parameters and environmental conditions. This work discusses a generic process to conduct a life consumption monitoring for electronic products. Two case studies on a circuit card assembly in an automobile under-hood environment are presented as application examples of the process. Temperature and vibration were identified as the dominant factors for the failure of the circuit card assembly. The environmental loads were monitored using a data recorder and the remaining life of the card assembly was estimated using physics-of-failure based stress and damage models. The predicted remaining life of the circuit card assembly correlated well with the measurement results.

Dynamic classification of groups through social network analysis and HMMs

Abstract: Social network analysis (SNA) represents interpersonal communications as directed graphs. SNA metrics quantify different aspects of a group's communication patterns. The goal of our work is to identify terrorist communications based on their atypical SNA metric values. The social structure of terrorist groups and other illicit organizations are distinguishable from normal groups by the fact that their metric values evolve differently over time. We employ hidden Markov models (HMMs) to identify groups with suspicious evolutions. The entire history of the social structure is used, instead of just viewing the structure at a single point in time. We motivate and present results from a case study using a simulation of suspicious groups communicating in a normal background population. We achieved 96% classification accuracy on novel synthetic data using two 35-state univariate HMMs trained to model normal and suspicious evolutions of the characteristic path length metric.

An unscented particle filter for GMTI tracking

Abstract: Ground moving target indicator (GMTI) tracking is often carried out using extended Kalman filters, as in the variable-structure interacting multiple-model (VS-IMM) filter. In some scenarios, however, this is considered to be inadequate. It has been shown that in this case, a particle filter can give better performance. Such a filter, the variable-structure multiple-model particle filter (VS-MMPF), is given in the literature. In this paper we present a new approach to solving the GMTI tracking problem using a particle filter. We have developed an unscented particle filter, where the particles model the uncertainty over the motion model while, conditional upon the model, the target state is modelled using an unscented Kalman filter. Simulation results show that the UPF-based filter gives performance similar to the VS-MMPF with significantly fewer particles and better results than the standard VS-IMM approach.

Avionics health management: searching for the prognostics grail

Abstract: The focus of this paper is to present the advances, benefits and challenges in measuring, monitoring and managing the health of aircraft avionics systems as well as the support equipment used to test these systems. Most people are skeptical when avionics and prognostics are used in the same sentence. For the purpose of this discussion, we will grant that most electronic discrete parts fail randomly. However, in the aircraft maintenance arena that point is moot because the lowest repairable level is the assembly on which those discrete parts reside. When an assembly fails or has an intermittent fault (resulting from aging solder connections or other environmental or mechanical factors), it is manifested as a system fault or failure. As degraded performance trends occur over time, there is an increased probability of predicting with reasonable confidence, when a given assembly is likely to experience an insipient fault or a cause a mission failure. While many of the current USAF maintenance metrics add no apparent value to prognostics capability, a few critical data elements are discussed. An optimum set of metrics is proposed through which the performance of avionics assemblies can be monitored. Considerable insight into the relative performance of a wide range of avionics assemblies has been gained through analysis of test parameters and failure information (typically not archived) that have been captured from automated test equipment (ATE). The automated methodology that captures statistically processes and archives test data from both the units under test (UUT) and the ATE instruments is described. The insight gained from this technique has led to cost avoidance in the tens of millions of dollars by reducing no faults found (NFF) occurrences, which, in turn, improves mission capability rates and reduces logistics support cost. Specific examples of these benefits to the USAF F-16 fleet are provided.

Pattern classification in social network analysis: a case study

Abstract: We present the methodology and results of a proof of concept study that characterized actors in a simulated dataset as terrorists or nonterrorists by applying statistical classifiers to their social network analysis (SNA) metric values. The simulated datasets modeled the social interactions that occur within Leninist cell organizations and those that occur in more typical social structures. Multivariate Bayesian classifiers operating on the actors' global betweenness centrality and local average path length achieved the best performance. These solved the three-class classification problem (cell leader, cell member, or non-terrorist) at 86% accuracy and the two-class classification problem (terrorist or non-terrorist) at 93% accuracy. An algorithm for defining local windows in multimodal social network graphs is also presented.

Experimental results from FLEXnav: an expert rule-based dead-reckoning system for Mars rovers

Abstract: This paper presents a proprioceptive position estimation system (PPE) with inertial measurement unit (IMU) uses fuzzy logic operations in conjunction with the expert rules for finer gradation called fuzzy logic expert navigation (FLEXnav) PPE system. The detailed experimental results obtained with our FLEXnav system integrated with our Mars rover clone Fluffy and operating in a Mars-like environment. The paper also introduces new methods for wheel slippage detection and correction, along with preliminary experimental results.

An authentication service against dishonest users in mobile ad hoc networks

Abstract: A mobile ad hoc network is a collection of wireless mobile nodes, dynamically forming a temporary network without the use of any existing network infrastructure or centralized administration It is an emerging technology for civilian and military applications However, security in mobile ad hoc networks is hard to achieve due to the vulnerability of the links, the limited physical protection of the nodes, and the absence of a certification authority or centralized management point Similar to other distributed systems, security in mobile ad hoc networks usually relies on the use of different key management mechanisms We exploit characteristics of an ad hoc network and present our authentication service to protect network security in the presence of dishonest users Nodes originally trustable in the network may become malicious due to sudden attacks, so an adequate security support for authentication to deal with dishonest users who issue false public key certificates is crucial We describe a new authentication service with a well-defined network model and a trust model These models allow nodes in the network to monitor and rate each other with an authentication metric We also propose a novel public key certificate operation, incorporating with a trust value update algorithm in public key authentication The authentication service we propose is able to discover and isolate dishonest users in the network Finally, we evaluate the proposed solution through simulation to demonstrate the effectiveness of the scheme

On the Hilbert-Huang transform data processing system development

Abstract: One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the fast Fourier transform (FFT). The Fourier view of nonlinear mechanics that had existed for a long time, and the associated FFT (fairly recent development), carry strong a-priori assumptions about the source data, such as linearity and of being stationary. Natural phenomena measurements are essentially nonlinear and nonstationary. A development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang transform (HHT) proposes an approach to the solution for the nonlinear class of spectrum analysis problems. Using the empirical mode decomposition (EMD) followed by the Hilbert transform of the empirical decomposition data (HT) as stated in N.E. Huang et al. (1998), N. E. Huang (1999), and N. E. Huang (2001), the HHT allows spectrum analysis of nonlinear and nonstationary data by using an engineering a-posteriori data processing, based on the EMD algorithm. This results in a non-constrained decomposition of a source real value data vector into a finite set of intrinsic mode functions (IMF) that can be further analyzed for spectrum interpretation by the classical Hilbert transform. This paper describes phase one of the development of a new engineering tool, the HHT data processing system (HHTDPS). The HHTDPS allows applying the HHT to a data vector in a fashion similar to the heritage FFT. It is a generic, low cost, high performance personal computer (PC) based system that implements the HHT computational algorithms in a user friendly, file driven environment. This paper also presents a quantitative analysis for a composite waveform data sample, a summary of technology commercialization efforts and the lessons learned from this new technology development.

Theory of synchronous averaging/sup /spl Omega//

Abstract: Synchronous averaging is commonly known as time synchronous averaging (TSA) but is applicable to many independent variable domains that demonstrate periodic signals of interest. An alternative domain of example is the spatial domain. The common use of the synchronous averaging technique is the attenuation of both non-coherent components and the non-synchronous components to negligible levels. A common rule of thumb is that the amount of attenuation is related to the reciprocal of /spl radic/N where N is the number of averages. This rule is highly representative for the non-coherent components but is not representative for the non-synchronous terms. This paper lays down a synchronous averaging theory in a one dimension domain for both the synchronous components and the non-synchronous components, with some interesting results. The paper is of interest to anyone who uses the synchronous averaging process.