INSIDE: A neuronet based hardware fault diagnostic system
Publication Type
Conference Proceeding Article
Publication Date
6-1990
Abstract
An inertial navigation system interactive diagnostic expert (INSIDE) was developed for troubleshooting an avionic line-replaceable unit, the inertial navigation system. INSIDE was designed based on a neural network model called neural-logic network. The knowledge base can be constructed using a neural-logic network by learning from past cases recorded in the workshop log book. To complement the connectionist knowledge base, a flowchart module which captures the knowledge of troubleshooting flowcharts was also implemented as part of the system. During operation, if the connectionist module fails to derive the solution, the user will be directed to the flowchart module for guidance. After the case is solved, it can be captured as a new example to be acquired by the connectionist module. Besides providing an economical way for developing fault diagnostic systems in general, the learning process of the system highly resembles the way an expert acquires knowledge through experience
Keywords
neural nets, aircraft instrumentation, expert systems, inertial navigation, knowledge acquisition
Discipline
Databases and Information Systems | Hardware Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of 1990 International Joint Conference on Neural Networks, San Diego, California, June 17-21
Volume
1
First Page
63
Last Page
68
Identifier
10.1109/IJCNN.1990.137546
Publisher
IEEE
City or Country
San Diego, USA
Citation
1