Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft
Electrical power systems play a critical role in spacecraft
and aircraft, and they exhibit a rich variety of failure modes.
This paper discusses electrical power system fault diagnosis
by means of probabilistic techniques. Specically, we discuss
our development of a diagnostic capability for an electrical
power system testbed, ADAPT, located at NASA Ames.
We emphasize how we have tackled two challenges, regarding
modelling and real-time performance, often encountered
when developing diagnostic applications. We carefully discuss
our Bayesian network modeling approach for electrical
power systems. To achieve real-time performance, we build
on recent theoretically well-founded developments that compile
a Bayesian network into an arithmetic circuit. Arithmetic
circuits have low footprint and are optimized for embedded,
real-time systems such as spacecraft and aircraft.
We discuss our probabilistic diagnostic models developed for
ADAPT along with successful experimental results.
Complete Metadata
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| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[
"026:00"
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"fn": "SCOTT POLL",
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"hasEmail": "mailto:scott.d.poll@nasa.gov"
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|
| description | Electrical power systems play a critical role in spacecraft and aircraft, and they exhibit a rich variety of failure modes. This paper discusses electrical power system fault diagnosis by means of probabilistic techniques. Specically, we discuss our development of a diagnostic capability for an electrical power system testbed, ADAPT, located at NASA Ames. We emphasize how we have tackled two challenges, regarding modelling and real-time performance, often encountered when developing diagnostic applications. We carefully discuss our Bayesian network modeling approach for electrical power systems. To achieve real-time performance, we build on recent theoretically well-founded developments that compile a Bayesian network into an arithmetic circuit. Arithmetic circuits have low footprint and are optimized for embedded, real-time systems such as spacecraft and aircraft. We discuss our probabilistic diagnostic models developed for ADAPT along with successful experimental results. |
| distribution |
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"@type": "dcat:Distribution",
"title": "2008AAAI_Mengshoel_DiagnosingFaultsElectricalPowerSystems.pdf",
"format": "PDF",
"mediaType": "application/pdf",
"description": "2008AAAI_Mengshoel_DiagnosingFaultsElectricalPowerSystems.pdf",
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| identifier | DASHLINK_865 |
| issued | 2013-12-18 |
| keyword |
[
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]
|
| landingPage | https://c3.nasa.gov/dashlink/resources/865/ |
| modified | 2025-03-31 |
| programCode |
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]
|
| publisher |
{
"name": "Dashlink",
"@type": "org:Organization"
}
|
| title | Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft |