Information Science

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

Gradual changes associated with aging are taken into account in the diagnostic process. A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection- and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs.

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Ground-Based Localization of Mars Rovers

The document discusses a procedure for localizing the Mars rovers in site frame, a locally defined reference frame on the Martian surface. MER onboard position within a site frame is estimated onboard and is based on wheel odometry. Odometry estimation of rover position is only reliable over relatively short distances assuming no wheel slip, sinkage, etc. As the rover traverses, its onboard estimate of position in the current site frame accumulates errors and will need to be corrected on occasions via relocalization on the ground (mission operations). The procedure provides a systematic process for ground operators to localize the rover. The method focuses on analysis of acquired images used to declare a site frame and images acquired post-drive. Target selection is performed using two main steps. In the first step, the user identifies features of interest from the images used to declare the current site. Each of the selected target’s position in site frame is recorded. In the second step, post-traverse measurements of the selected features’ positions are recorded again, this time in rover frame, using images acquired post-traverse. In the third step, we transform the post-traverse target’s positions to local level frame. In the fourth step, we compute the delta differences in the pre- and post-traverse target’s position. In the fifth step, we analyze the delta differences with techniques that compute their statistics to determine the rover’s position in the site frame.

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Methodology for Designing Fault-Protection Software

A document describes a methodology for designing fault-protection (FP) software for autonomous spacecraft. The methodology embodies and extends established engineering practices in the technical discipline of Fault Detection, Diagnosis, Mitigation, and Recovery; and has been successfully implemented in the Deep Impact Spacecraft, a NASA Discovery mission. Based on established concepts of Fault Monitors and Responses, this FP methodology extends the notion of Opinion, Symptom, Alarm (aka Fault), and Response with numerous new notions, sub-notions, software constructs, and logic and timing gates. For example, Monitor generates a RawOpinion, which graduates into Opinion, categorized into no-opinion, acceptable, or unacceptable opinion. RaiseSymptom, ForceSymptom, and ClearSymptom govern the establishment and then mapping to an Alarm (aka Fault). Local Response is distinguished from FP System Response. A 1-to-n and n-to-1 mapping is established among Monitors, Symptoms, and Responses. Responses are categorized by device versus by function. Responses operate in tiers, where the early tiers attempt to resolve the Fault in a localized step-bystep fashion, relegating more system-level response to later tier(s). Recovery actions are gated by epoch recovery timing, enabling strategy, urgency, MaxRetry gate, hardware availability, hazardous versus ordinary fault, and many other priority gates. This methodology is systematic, logical, and uses multiple linked tables, parameter files, and recovery command sequences. The credibility of the FP design is proven via a fault-tree analysis “top-down” approach, and a functional fault-mode-effects-andanalysis via “bottoms-up” approach. Via this process, the mitigation and recovery strategy( s) per Fault Containment Region scope (width versus depth) the FP architecture.

Posted in: Information Sciences, Briefs, TSP

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Generation of Data-Rate Profiles of Ka-Band Deep-Space Links

A short report discusses a methodology for designing Ka-band Deep-Space-to-Earth radio-communication links. This methodology is oriented toward minimizing the effects of weather on the Ka-band telecommunication link by maximizing the expected data return subject to minimum link availability and a limited number of data rates. This methodology differs from the current standard practices in which a link is designed according to a margin policy for a given link availability at 10° elevation. In this methodology, one chooses a data-rate profile that will maximize the average data return over a pass while satisfying a minimum- availability requirement for the pass, subject to mission operational limititations expressed in terms of the number of data rates used during the pass. The methodology is implemented in an intelligent search algorithm that first finds the allowable datarate profiles from the mission constraints, spacecraft-to-Earth distance, spacecraft EIRP (effective isotropic radiated power), and the applicable zenith atmospheric noise temperature distribution, and then selects the best data rate in terms of maximum average data return from the set of allowable data-rate profiles.

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Education and Training Module in Alertness Management

An interactive Web-based General Aviation version of the module is now available for FAA WINGS credit. The education and training module (ETM) in alertness management has now been integrated as part of the training regimen of the Pilot Proficiency Awards Program (“WINGS”) of the Federal Aviation Administration. Originated and now maintained current by the Fatigue Countermeasures Group at NASA Ames Research Center, the ETM in Alertness Management is designed to give pilots the benefit of the best and most recent research on the basics of sleep physiology, the causes of fatigue, and strategies for managing alertness during flight operations.

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Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data

Researchers at JPL and Arizona State University conducted a comparative study of three candidate algorithms for estimating components of the Martian atmosphere, using raw (uncalibrated) data collected by the Thermal Emission Imaging System (THEMIS). THEMIS is an instrument onboard the Mars Odyssey spacecraft that acquires image data in five visible and nine infrared (IR) wavelength bands. The algorithms under study used data collected from eight of the nine IR bands to estimate the dust and water ice content of the atmosphere. Such an algorithm could be used in onboard data processing to trigger other algorithms that search for features of scientific interest and to reduce the volume of data transmitted to Earth.

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Computing a Stability Spectrum by Use of the HHT

Unlike in the predecessor method, the mathematical sign of the damping is retained. The Hilbert-Huang transform (HHT) is part of the mathematical basis of a method of calculating a stability spectrum. This method can be regarded as an extended and improved version of a prior HHT-based method of calculating a damping spectrum. In the prior method, information on positive damping (which leads to stability) and negative damping (which leads to instability) becomes mixed into a single squared damping loss factor. Hence, there is no way to distinguish between stability and instability by examining a damping spectrum. In contrast, in the present stability-spectrum method, information on the mathematical sign of the damping is retained, making it possible to identify regions of instability in a spectrum. This method is expected to be especially useful for analyzing vibration- test data for the purpose of predicting vibrational instabilities in structures (e.g., flutter in airplane wings).

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