Abstract
The discrete-event nature of on-line data from automated manufacturing system offers many challenges for on-line fault detection. In this paper, the template monitoring method is developed as a simple but versatile method of fault monitoring using discrete event signals. This monitoring method is easily distributable, suitable for monitoring highly concurrent systems, and has low computational requirements. This paper describes template monitoring and summarizes analytical results on generating templates from timed automaton models.
| Original language | English |
|---|---|
| Pages | 65-69 |
| Number of pages | 5 |
| State | Published - 1994 |
| Event | 1994 AAAI Spring Symposium - Palo Alto, United States Duration: Mar 21 1994 → Mar 23 1994 |
Conference
| Conference | 1994 AAAI Spring Symposium |
|---|---|
| Country/Territory | United States |
| City | Palo Alto |
| Period | 3/21/94 → 3/23/94 |
Bibliographical note
Publisher Copyright:© 1994, AAAI (www.aaai.org). All rights reserved.
Funding
This work is supported in part by NASA grant NGT-40049, Rockwell International, NSF grant ECS-9308737, and the Center for Robotics and Manufacturing Systems at the University of Kentucky. An automatedb ottling line is showni n figure 1. As bottles enter the conveyor,t hey pass a proximitys witch which generates an event PS 1". A limit switch is tripped (LS T) whent he bottle enters the fill station. The fill valve is then opened (FV T). Whenth e fluid *This worki s supported in part by NASgr ant NGT-40049, RockwellI nternational, NSFg rant ECS-9308737, and the Center for Robotics and ManufacturingS ystems at the Universityo f Kentucky.
| Funders | Funder number |
|---|---|
| Center for Robotics and Manufacturing Systems | |
| Center for Robotics and ManufacturingS ystems | |
| NASgr | |
| NSFg | |
| Rockwell International Corporation | |
| U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China | ECS-9308737 |
| U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China | |
| National Aeronautics and Space Administration | NGT-40049 |
| National Aeronautics and Space Administration |
ASJC Scopus subject areas
- Artificial Intelligence