Model-Based Assurance of Diagnostic Procedures for Complex Systems

Abstract

Verifying diagnostic procedures for complex systems is hard and labor-intensive. Usually this verification is accomplished primarily through extensive review of the procedures by experts. We aim to augment this review process by using insights from comparing the diagnostic steps described in the procedural definitions with diagnostics information derived from existing models of the system. These comparisons offer various conformance checks between the manually developed diagnostic procedures and the diagnostic trees autogenerated from the diagnostic system models. We previously described our DTV (Diagnostic Tree for Verification) technique based on these comparisons. This paper describes an extension to DTV, and reports results of an application of DTV to a representative system's diagnostic procedures. Specifically, it outlines four analyses (branch analysis, root cause coverage, path verification, and efficiency) that can be performed using DTV; illustrates the process for applying DTV; and reports results from our application of DTV to assure fifteen of the procedures developed for diagnosing problems in an electrical power system testbed for spacecraft.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2010
Accession Number
ADA562751

Entities

People

  • Martin S. Feather
  • Robyn Lutz
  • Tolga Kurtoglu

Organizations

  • National Aeronautics and Space Administration

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Aerospace Craft
  • Calibration
  • California
  • Complex Systems
  • Computer Programs
  • Control Systems
  • Data Acquisition
  • Detectors
  • Efficiency
  • Failure Mode And Effect Analysis
  • Instructions
  • Jet Propulsion
  • Spacecraft
  • United States
  • Vehicles
  • Verification

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Software Engineering.
  • Solar Photovoltaics and Thermoelectric Devices.

Technology Areas

  • Space