Sign in
Author
|
Conference
|
Journal
|
Organization
|
Year
|
DOI
Look for results that meet for the following criteria:
since
equal to
before
between
and
Search in all fields of study
Limit my searches in the following fields of study
Agriculture Science
Arts & Humanities
Biology
Chemistry
Computer Science
Economics & Business
Engineering
Environmental Sciences
Geosciences
Material Science
Mathematics
Medicine
Physics
Social Science
Multidisciplinary
Keywords
(6)
Knowledge Base
Machine Tool
Multiprocessor Architecture
Physical Model
Signal Processing
Real Time
Subscribe
Academic
Publications
A knowledge-based supervision model for machine tools
A knowledge-based supervision model for machine tools,10.1109/CMPSAC.1989.65182,TAEHWAN YOON,JOSE C. PRINCIPE
Edit
A knowledge-based supervision model for machine tools
(
Citations: 2
)
BibTex
|
RIS
|
RefWorks
Download
TAEHWAN YOON
,
JOSE C. PRINCIPE
The knowledge-based supervision system described is intended to detect cutter damages in milling machines, using x-axis and y-axis displacement signals. The model hierarchically integrates real-time
signal processing
algorithms in a knowledge-based processing environment where rules and objects coexist. A deeply coupled, numeric/symbolic model is developed. It incorporates physical models and empirical knowledge. It is implemented in a
multiprocessor architecture
Conference:
International Computer Software and Applications Conference - COMPSAC
, 1989
DOI:
10.1109/CMPSAC.1989.65182
Cumulative
Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
(
ieeexplore.ieee.org
)
(
ieeexplore.ieee.org
)
Citation Context
(1)
...Other work in this area that makes use of neural networks are [19], [20], [42], and [
48
]...
Les E. Atlas
,
et al.
Self-organizing feature maps and hidden Markov models for machine-tool...
References
(16)
Population-Based Outcomes Following Endovascular and Open Repair of Ruptured Abdominal Aortic Aneurysms
(
Citations: 14
)
Kristina A. Giles
,
Allen D. Hamdan
,
Frank B. Pomposelli
,
Mark C. Wyers
,
Suzanne E. Dahlberg
,
Marc L. Schermerhorn
Journal:
Journal of Endovascular Therapy - J ENDOVASCULAR THERAPY
, vol. 16, no. 5, pp. 554-564, 2009
Collected world and single center experience with endovascular treatment of ruptured abdominal aortic aneurysms
(
Citations: 13
)
Frank J. Veith
,
Mario Lachat
,
Dieter Mayer
,
Martin Malina
,
Jan Holst
,
Manish Mehta
,
Eric L. G. Verhoeven
,
Thomas Larzon
,
Stefano Gennai
,
Gioacchino Coppi
,
Evan C. Lipsitz
,
Nicholas J. Gargiulo
http://academic.research.microsoft.com/io.ashx?type=5&id=32124637&selfId1=0&selfId2=0&maxNumber=12&query=
Journal:
Annals of Surgery - ANN SURG
, vol. 250, no. 5, pp. 818-824, 2009
Ruptured Endovascular Abdominal Aortic Aneurysm Repair: Part II
(
Citations: 2
)
Joseph J. Ricotta II
,
Rafael D. Malgor
,
Gustavo S. Oderich
Journal:
Annals of Vascular Surgery - ANN VASCULAR SURG
, vol. 24, no. 2, pp. 269-277, 2010
Hybrid Procedures for Thoracoabdominal Aortic Aneurysms
(
Citations: 6
)
Mark A. Farber
,
Peter F. Ford
Journal:
Seminars in Vascular Surgery - SEMIN VASC SURG
, vol. 22, no. 3, pp. 140-144, 2009
Fenestrated and Branched Stent Grafts
(
Citations: 9
)
J. J. Ricotta
,
G. S. Oderich
Journal:
Perspectives in Vascular Surgery and Endovascular Therapy
, vol. 20, no. 2, pp. 174-187, 2008
Sort by:
Citations
(2)
Self-organizing feature maps and hidden Markov models for machine-tool monitoring
(
Citations: 31
)
Les E. Atlas
,
Gary D. Bernard
Journal:
IEEE Transactions on Signal Processing - TSP
, vol. 45, no. 11, pp. 2787-2798, 1997
Knowledge representation in machine tool supervision systems
Jose C. Principe
,
Taehwan Yoon
Conference:
IEEE International Symposium on Intelligent Control - ISIC
, 1990