1
Towards a Fault Management Analysis Tool for Model Centric
Systems
Ksenia Kolcio
1
, Maurice Prather
2
, David Wagner
3
, Maged Elaasar
3
, Narek Shougarian
3,
1,2
Okean Solutions, Inc, Seattle, WA, 98122, USA
ksenia@okean.solutions
maurice@okean.solutions
3
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA
David.Wagner@jpl.nasa.gov
Maged.Elaasar@jpl.nasa.gov
Narek.Shougarian@jpl.nasa.gov
ABSTRACT
In an effort to effectively develop more complex spacecraft
fault management (FM) systems new technologies are sought
to enable rapid diagnostic model generation and validation,
and provide tools to perform FM analyses Model-based
Systems Engineering approaches to FM system development
are uniquely suited to be combined with model-based tools
currently utilized in the design of other parts of flight
systems. Combined tools utilizing information from a
common system model can reduce design inconsistencies and
gaps in analyses. Tighter integration of FM with other
system-level and subsystem-level hardware/software
development activities allows crucial redundancy and sensor
placement trades to be performed earlier and throughout the
mission lifecycle.
Our work has been towards the integration of a model-based
fault management tool suite called MONSID®, with JPL’s
Computer Aided Engineering for Systems ARchitecture
(CAESAR ) platform as a way to improve FM system
modeling and analysis. MONSID relies on application-
specific models of the system being monitored. MONSID
models consist of interconnected elements representing
system hardware and measurement/command input points,
called the topology. Model topology design is currently a
manual process and often relies heavily on paper
documentation such as hardware/software specs, engineering
drawings, and interface control documents. CAESAR is a
semantically- driven toolchain for model-based system
engineering. At the core is a system model expressed in the
Ontological Modeling Language (OML). It is intended to
support semantic modeling, consistency validation, and
continuous integration.
A goal of the combined toolset is to automate FM model
development by directly extracting models from CAESAR
and then analyzing them in MONSID. Analyses currently
available in MONSID include model topology inspection and
validation and fault isolation capability based on sensor
placement. While we have focused on two specific tools, the
integration approaches can be leveraged by other
semantically driven model-centric platforms and tools.
This paper describes the evolution of our integration
approaches as we evaluated different insertion points in the
CAESAR toolchain with respect to MONSID model
requirements. The MONSID-CAESAR tool is demonstrated
on a simplified example of a spacecraft heat reclamation
system. Results of the generated MONSID model are
discussed, including levels of automation achieved and
information surfaced to the users about the extracted model
topology.
1. INTRODUCTION
New technologies are sought to effectively manage and
streamline increasingly complex fault management (FM)
systems, enable rapid diagnostic model generation and
validation, and provide tools to perform FM analyses and
trades e.g., fault isolation capability, FM model validation,
and sensor placement.
Traditional fault detection systems monitor signals for known
out of limit levels (e.g. over temperatures, excessive rates,
stale data). Such monitors are designed to detect specific fault
conditions. In contrast, the model-based fault detection
approach utilized in this work relies on exposing deviations
from modeled behavior which is assumed to be correct and
as intended.
