RÉSUMÉ
John P. H. Steele
Laboratory for Robotics and Intelligent Machines
Associate Professor - Engineering Division
Colorado School of Mines
Golden, Colorado 80401
Phone: (303) 273-3663
I.
II.
Registered Professional Engineer, Colorado
Education
1988
1986
1970
Ph.D.
M.S.
B.S.
Engineering, University of New Mexico.
Mechanical Engineering, University of New Mexico.
Physics, cum laude, New Mexico State University.
III.
Work Experience
A.1992 - Present
- Laboratory for Robotics and Intelligent Machines
Conduct research on Intelligent Automated Systems, with a focus on applications to robots and intelligent
process control, especially for the resource industries. Design, fabrication, assembly and test of new robot
systems, both mobile platforms and manipulators, simultaneous localization and mapping for both ground based
and aerial vehicles, robotic welding especially weld quality assessment in realtime, and intelligent control of the
welding process using vision. Develop new techniques for detecting and assessing the health condition of
machinery, on-line in real-time. Direct and manage graduate and undergraduate students working in the
laboratory. Pursue grant opportunities from industry and government sources. Design and develop new sensor
systems, new methods and techniques for data analysis and interpretation, and new methods and approaches to
system control, and health assessment.
B.Research interests – Development of Intelligent Machines
The focus of our research in the laboratory is on SHARP (system health assessment and real-time prediction)
systems and new robot systems. Our goal is to develop intelligent systems that can detect and assess the
operational condition of machines and other equipment automatically, and make predictions of future failures.
This work necessarily requires a very strong understanding of the fundamentals of machine design, dynamics
and vibrations, sensors, signal conditioning, data acquisition, and data interpretation. In addition, modes of
failure and their indicators are very important, as are computational techniques to assess machine health and
predict failure. Modeling of mechanical systems provides a fundamental basis for understanding the expected
behavior of systems as well as changes that will occur over time.
C.Industrial Activities
I have had the opportunity to work with a number of companies, organizations and individuals on projects and
as a consultant, these include: NIOSH, Lockheed Martin, Intel, Caterpillar, Sandia National Labs, Stolar
Horizon, Department of Energy, Coors, Unique Mobility, MTS Systems, McDonnell Douglas, DARPA, Dept.
of Justice, Loral Aerospace, Denver Veterans Hospital, Children’s Hospital, Steward and Stevenson, and Wolf
Robotics. In addition, I have been retained as an expert in forensic engineering analysis for a number of
mechanical engineering analyses, and design problems. I’m a past chair of the Colorado Section of the
American Welding Society and the Colorado Section of the American Society of Mechanical Engineers.
D.Skills
I have been involved in the design of a large number of systems, from initial concept to fabrication and
production. I have developed a number of computer based data acquisition systems. I have extensive
experience in programming, especially real-time systems, data acquisition, and controls for robots. Languages
include Python, C, LabVIEW, Java, C++, Visual Basic, FORTRAN, and Lisp. I also have significant
experience with Finite Element Modeling and analysis, and use of various mathematical tools including
Mathematica, Matlab, Mathcad, Excel, and Simulink. Drawing tools include SolidWorks, Sketchup, and
AutoCAD.
III.
Related Publications
A.
Journals
• Moore, K. L., Weiss, M. D., and Steele, J. P., Meehan, C., Hulbert, J., Larson, E., Weinstein, A., “Experiments
with Autonomous Mobile Radios for Wireless Tethering in Tunnels”, Journal of Defense Modeling and
Simulation: Applications, Methodology, Technology 1–14 DOI: 10.1177/1548512910393375, Jan 26, 2011.
•
Schwendeman, J., Dreyer, C., Steele, J., “Design Considerations for the Development of a Wire-Based Rock
Cutting Mechanism for Space Exploration.” ASME Journal of Mechanical Design, Dec 2010.
•
G. Schwab, J. P. H. Steele, T. L. Vincent, “Vision-Based Spatter Classification for Contaminant Detection,”
2009, The Welding Journal, June 2009, pp121s-130s.
•
“Development of closed-loop control of robotic welding processes,” J. P. H. Steele, C. Mnich, C. Debrunner, T.
Vincent and S. Liu, 2005, Industrial Robot, Vol. 32, No. 4, pp350-355.
•
“Stereo Vision in LHD Automation”, M. Whitehorn, T. Vincent, C. Debrunner, and J. Steele, IEEE
TRANSACTIONS on Industry Applications, Vol. 39, No. 1, pp. 21-29, Jan./Feb. 2003.
•
“Fiber Optic Sensor Development for Real-Time In-Situ Composite Cure Monitoring”, Y. M. Liu, C. Ganesh,
J.P.H. Steele, and J. E. Jones, Journal of Composite Materials, Vol. 31 No. 1/1997, pp. 87-102.
•
“Control and Scale Model Simulation of Sensor-Guided LHD Mining Machines,” John Steele, C. Ganesh, and
Arnold Kleve, IEEE Transactions on Industrial Applications, Vol. 29, Issue: 6, 1993.
•
“Predicting Trajectories Using Recurrent Neural Networks”, Gordon, A., John P. H. Steele, and Kathy
Rossmiller, Heuristics; The Journal of Knowledge Engineering, Vol. 5, No. 3, Fall 1992, pp. 80-89.
•
“Control of Mobile Robots”, John P.H. Steele and Nader D. Ebrahimi, International Journal of Robotics and
Automation, Vol. 1 No. 2, pp. 40-46, 1986.
B.
!
Reviewed Conference Proceedings
•
Carolina Payares-Asprino, John P H Steele, and Lusia F. Espinosa, “Optimum Design Based on Mathematical
Model and Neural Network to Predict Reinforcement for Duplex Fillet Joints” Session 8, AWS Professional
Program 2013, FABTECH, Nov. 18-21, 2013
•
Andrew Neill and John Steele, “Characterization of Robotic Gas Metal Arc Welding” Session 6, AWS
Professional Program 2013, FABTECH, Nov. 18-21, 2013
•
A. Neill and J. Steele, “Identification and Calibration of Automated GMAW Processes” AWS 2012 Annual
Conference, Nov. 12-14, 2012
•
M. Gaztañaga, A Neill, J Steele “Visual Observation and Analysis of Gas Metal Arc Weld Pool”, AWS 2012
Annual Conference, Nov. 12-14, 2012
•
B. Geels and J. Steele, “Reliability Model Development and Sensor System Optimization of the Gearbox
Reliability Collaborative’s 750kW Test Gearbox”, MFPT, Dayton, OH, April 23-26, 2012.
•
B. Walter, J. Steele, and E. A. Gharahbagh. “Adding Smarts to Cutting Tools.” North American Tunneling 2012.
Indianapolis, IN, June 24-27, 2012.
•
J.P.H. Steele, “Learning Machines for Weld Parameters”, 2011, AWS Fabtech.
•
Dreyer, C.; Zacny, K.; Skok, J.; Steele, J.; Paulsen, G.; Szczesiak, M.; Nakagawa, M.; Schwendeman, J.,
“Progress on the Development of a Thin Section Sample Preparation Device for Space Exploration,” 40th Lunar
and Planetary Science Conference, (Lunar and Planetary Science XL), March 23-27, 2009, Contribution No.
2463.
•
C. Payares-Asprino and J. P. H. Steele “Optimization of GMAW Welding Parameters for Duplex Stainless Steel
Weld Mechanical Properties,” 2009, PVP2009-77203 ASME PVP 2009 Conference, July 26-30, Prague, Czech
Republic.
•
“Mathematical Modeling of Weld Bead Profile Shapes: Modeling and Measurements, J. P. H. Steele and C.
Payares-Asprino, ,Session:13F, AWS 2008 Annual Conference, Oct 6-8, Las Vegas, NV.
•
“Optimization of GMAW Welding Parameters in Duplex Stainless Steel Welds,” C. Payares-Asprino and J. P.
H. Steele , Session:13C, AWS 2008 Annual Conference, Oct 6-8, Las Vegas, NV.
•
“Robotic Thin Section Sample Preparation Device for In Situ Planetary Exploration,” Dreyer, C B, Zacny, K,
Skok, J., Steele, J., Paulsen, G., Nakagawa, M., Schwendeman, J., Carrell, T., Szczesiak, M., Eos Trans. AGU,
89(53), Fall Meet. Suppl., Abstract P53C-1463, (2008).
•
“Chip Formation in Mechanical Excavation: An Indicator of Machine Performance”, John P. H. Steele,
Benjamin H. Miller, and M. Ugur Ozbay, Preprint # 02-122, SME 2002 Annual Meeting, Phoenix AZ, Feb.
2002.
•
“Stereo vision in LHD automation,” M. Whitehorn, T. Vincent, C. Debrunner, and J. Steele presented at IEEE,
IAS 2001 Annual Meeting, Chicago, Illinois, 2001.
•
“Developing Stereovision and 3D Modeling for LHD Automation,” John Steele, Chris Debrunner, Tyrone
Vincent, and Mark Whitehorn, 6th International Symposium on Mine Mechanization and Automation,
Johannesburg, South Africa, September, 2001, pp 209-216.
•
“LHD Loading: Moving from Teleoperation to Automation,” J.P.H. Steele, C.H. Debrunner, T.L. Vincent, and
M.A. Whitehorn, Proceedings of the 4th Regional Symposium on Computer Applications in the Mineral
Industries, APCOM 2001, Tampere, Finland, 3-5 September 2001, pp 201-211.
•
“Developing Real-time Diagnostics for Cutting Heads on Underground Mining Machines,” John P. H. Steele,
M. U. Ozbay, and Benjamin Miller, Proceedings of the 4th Regional Symposium on Computer Applications in
the Mineral Industries, APCOM 2001, Tampere, Finland, 3-5 September 2001, pp 59-64.
•
“Robotics for Underground Hardrock Mining” J. P.H. Steele, C. Debrunner, T. Vincent, and M. Whitehorn, 2000
Society of Mining Engineers Annual Conference, Preprint 00-6, April 2000.
•
“Online Machine Health Assessment Using Oil Analysis,” John P. H. Steele and Michelle Archuleta, P/PM
Technology, Vol. 12, Issue 5, October 1999, pp 36-39.
•
“Predicting Failure Using Online Oil Condition Monitoring”, Michelle R. Archuleta and John P. H. Steele,
Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 8, Dagli, Akay, Buczak, Ersoy, &
Fernandez Editors, ASME Press, 1998, pp. 697-702.
•
“Strategies for Enhancing Reliability: Automated Condition Monitoring Using Expert Systems to Detect
Cavitation in Hydraulic Pumps”, John P.H. Steele, Michelle Archuleta, Galen Brown, Roman Kucbel, and Tim
Seifert, Eighth Annual Predictive Maintenance Technology National Conference, Indianapolis, IN, December,
1996, Technical Papers - pp. 34-38.
•
“Managing Uncertainty in Predictive Maintenance Systems: A Decision Analysis Approach”, Michael R. Walls
and John P.H. Steele, Eighth Annual Predictive Maintenance Technology National Conference, Indianapolis, IN,
December, 1996, Technical Papers - pp. 48-53.
•
“Fuzzy Logic Processing and Dynamic Alarm Handling for Real-Time Machine Health Monitoring”, Tim D.
Seifert and John P. H. Steele, Intelligent Engineering Systems Through Artificial Neural Networks, Vol. 6,
Dagli, Akay, Chen, Fernandez, & Ghosh, Editors, ASME Press, 1996, pp. 231-236.
•
“System Health Assessment for Robots in Critical Environments”, John P. H. Steele, Michelle Archuleta, Galen
Brown, Tom Drouillard, Dirk Schlief, Tim D. Seifert, in the Proceedings of Robots for Challenging
Environments II, ASCE, Albuquerque, NM, July 1996, pp. 262-275.
•
“System Health Assessment and Predictive Maintenance”, John P.H. Steele, Michelle Archuleta, Galen Brown,
and Tim Seifert, Seventh Annual Predictive Maintenance National Conference, Indianapolis, IN, December,
1995, pp. T8-19.
•
“Intelligent Process Monitoring for Carbon Fiber/Epoxy Composite Manufacturing”, John P. H. Steele, Deepa
Mishra, and Chidambar Ganesh, Proceedings of the ASME Materials Division, Vol.2, Intelligent
Manufacturing and Material Processing, MD-V0l. 69-2, 1995 ASME International Mechanical Engineering
Congress and Exposition, San Francisco, CA, November 1995, pp. 899-909.
•
“Control and Scale Model Simulation of Sensor-Guided LHD Mining Machines,” John Steele, Arnold Kleve,
and C. Ganesh, Proceedings of the 1991 IEEE Industrial Applications Society Annual Conference, Dearborn
MI, Oct. 1991.
•
“Modeling and Sensor-Based Control of an Autonomous Mining Machine”, John P. H. Steele, Robert H. King,
and William Strickland, International Symposium on Mine Mechanization and Automation, Vol. 1, pp.
6-55-6-67, 1990.
•
“Mining and Excavating Systems for a Lunar Environment”, W. R. Sharp, J. P. H. Steele, B. C. Clark, Space 90,
Albuquerque, NM, April 1990.