Agenda

Agenda – Overview

Registrants at PHM16 can also attend talks of the DX16 conference on site. Networking breaks, keynotes and the Tuesday reception will also be joint events. For the DX16 agenda see: http://dx-2016.org/program.php



Venue Map




Detailed Agenda


Sunday, October 2, 2016 — Doctoral Symposium

Monday, October 3, 2016 — Opening Remarks, Tutorials, Panels, Technical Paper Sessions, Welcome Reception

Tuesday, October 4, 2016 — Luminary, Keynote, Panels, Technical Paper Sessions, Technology Demos, Poster Session

Wednesday, October 5, 2016 — Luminary, Panel, Technical Paper Sessions, Technology Demos, Banquet Dinner

Thursday, October 6, 2016 — Joint PHM/DX Keynote, Technical Paper Sessions, Panel Sessions, Technology Demos, Closing Remarks


Sunday, October 2, 2016 Location
12:00–17:00 Registration 3rd Floor Foyer
13:00–15:00 Doctoral Symposium Session 1 Aspen AB
15:00–15:30 Break
15:30–17:30 Doctoral Symposium Session 2 Aspen AB
17:30–18:30 Doctoral Symposium Dinner
18:30–20:30 Doctoral Symposium Session 3 Aspen AB
Monday, October 3, 2016 Location
7:00–17:00 Registration 3rd Floor Foyer
8:00–9:45 Tutorial Session 1A: Diagnostics Cripple Creek A
8:00–9:45 Tutorial Session 1B: An Introduction to Data-Driven Prognostics of Engineering Systems Cripple Creek B
9:45–10:15 Break 3rd Floor Foyer
10:15–12:00 Tutorial Session 2A: Security Prognostics Cripple Creek A
10:15–12:00 Tutorial Session 2B: Big Data Analytics Cripple Creek B
12:00–13:00 Lunch on your own
13:00–13:45 Opening Remarks Crystal Ballroom
13:00–13:45 Opening Keynote: Dr. Jay Lee, University of Cincinnatti Crystal Ballroom
13:45–15:30 Session 1A: Aviation I
Session Chair: Rhonda Whalthall–UTAS
Cripple Creek A
  Improved Time-Based Maintenance in Aeronautics with Regressive Support Vector Machines
Marcia Baptista1, Ivo P. de Medeiros2, Joao P. Malere3, Helmut Prendinger4, Cairo L. Nascimento Jr5, Elsa Henriques6
1,6 Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, 1049-001, Portugal
2,3 Technol. Dev. Dept., Embraer SA, Sao Jose dos Campos, Brazil
5 Instituto Tecnologico de Aeronautica (ITA), 12228-900, Sao Jose dos Campos-SP, Brazil
4 National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
 
  Flight Anomaly Tracking for Improved Situational Awareness: Case Study of Germanwings Flight 9525
Murat Yasar1
1 United Technologies Research Center, East Hartford, CT, 06118, USA
  Anomaly Detection and Fault Disambiguation in Large Flight Data: A Multi-modal Deep Auto-encoder Approach
Kishore K. Reddy1, Soumalya Sarkar2, Vivek Venugopalan3, Michael Giering4
1,2,3,4 United Technologies Research Center (UTRC), East Hartford, CT, USA
13:45–15:30 Session 1B: Diagnostics I
Session Chair: Abhinav Saxena –GE
Cripple Creek B
  Solenoid Valve Diagnosis for Railway Braking Systems with Embedded Sensor Signals and Physical Interpretation
Boseong Seo1, Soo-Ho Jo2, Hyunseok Oh3, Byeng D. Youn4
1,2,3,4 Department of Mechanical Engineering, Seoul National University
 
  Spur Gear Electrical Pitting Wear Diagnostic from Tribological Responses
Surapol Raadnui1
1 Department of Production Engineering, King Mongkut’s University of Technology North Bangkok (KMUTNB), 1518, Pracharaj 1 Road, Bang-Sue, District, Bangkok, Postal Code 10800, Bangkok, Thailand, Email address:
  Integration of Failure Assessments into the Diagnostic Process
Roxane Koitz1, Franz Wotawa2
1,2 Institute for Software Technology, Graz, Styria, 8010, Austria
13:45–15:30 Panel Session 1: PHM For Human Assets I Crestone A
15:30–15:45 Break 3rd Floor Foyer
15:45–17:30 Session 2A: Systems I
Session Chair: Kirtland McKenna–Colorado School of Mines
Cripple Creek A
  Autonomous Operations System: Development and Application
Jaime A. Toro Medina1, Kim N. Wilkins2, Mark Walker3, Gerald M. Stahl4
1,4 NASA Kennedy Space Center, Kennedy Space Center, Florida, 32899, United States of America
2 General Atomics, 3550 General Atomics Court, San Diego, California, 92121, United States of America
3 D2K Technologies
 
  Distributed Real Time Compressor Blade Health Monitoring System
LiJie Yu1, Sachin Shrivastava2
1 General Electric Power Services Engineering, Atlanta, GA 30339, USA
2 General Electric Power Services Engineering, Bangalore, KA 560066, India
  An Architectural Framework for Reliability Centered Maintenance and Remote Maintenance Monitoring of Complex Distributed Systems
Henry Silcock1, Becky Norman2, Jason Ricles3
1,2,3 Mikros Systems Corporation, Fort Washington, PA 19034, USA
15:45–17:30 Session 2B: Features I
Session Chair: Ravi Rajamani–drR2 Consulting
Cripple Creek B
  Leakage Detection of Steam Boiler Tube in Thermal Power Plant Using Principal Component Analysis
Jungwon Yu1, Jaeyel Jang2, Jaeyeong Yoo3, June Ho Park4, Sungshin Kim5
1,4,5 Department of Electrical and Computer Engineering, Pusan National University, Busan, 46241, South Korea
2 Technical Solution Center, Technology & Information Department, Korea East-West Power Co., Ltd., Dangjin
3 CTO, XEONET Co., Ltd., Seongnam, Gyeonggi-do, 13216, South Korea
 
  An Overview of Useful Data and Analyzing Techniques for Improved Multivariate Diagnostics and Prognostics in Condition-Based Maintenance
Carolin Wagner1, Philipp Saalmann2, Bernd Hellingrath3
1,2,3 Westfälische Wilhelms-Universität Münster, 48149 Münster, Germany
13:45–15:30 Panel Session 1 (cont.): PHM For Human Assets II Crestone A
17:30–19:30 Opening Welcome Reception Crystal Ballroom Foyer
Tuesday, October 4, 2016 Location
7:00–17:00 Registration 3rd Floor Foyer
7:45–8:00 Continental Breakfast 3rd Floor Foyer
8:00–8:45 Opening Remarks Crystal Ballroom
8:00–8:45 Luminary Presentation: Dr. David Hilmers, former Astronaut, Baylor College of Medicine Crystal Ballroom
8:45–10:15 Session 3A: Prognostics I
Session Chair: Kai Goebel–NASA Ames
Cripple Creek A
  An Inference-based Prognostic Framework for Health Management of Automotive Systems
Chaitanya Sankavaram1, Anuradha Kodali2, Krishna Pattipati3, Satnam Singh4, Yilu Zhang5, Mutasim Salman6
1,2,3 Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
2 University of California Santa Cruz, NASA Ames Research Center, Moffett Field, CA, 94035
4 CA Technologies, Bangalore, Karnataka 560017, India
1,5,6 Vehicle Systems Research Lab, General Motors Global R&D, Warren, MI 48090, USA
 
  PHM Decision Support under Uncertainty
Murat Yasar1, Teems E. Lovett2
1,2 United Technologies Research Center, East Hartford, CT, 06118, USA
  A New Prognostics Approach for Bearing based on Entropy Decrease and Comparison with existing Methods
Seokgoo Kim1, Sungho Park2, Ju-Won Kim3, Junghwa Han4, Dawn An5, Nam Ho Kim6, Joo-Ho Choi7
Dept. of Aerospace and Mechanical Engineering, Korea Aerospace University, Goyang-City, Gyeonggi-do Korea
3,4 Korea railroad corporation, Daejeon, Korea
5,6 Mechanical & Aerospace Eng. University of Florida, Gainesville, FL, USA
7 School of Aerospace and Mechanical Engineering, Korea Aerospace University, Goyang-City, Gyeonggi-do Korea
8:45–10:15 Session 3B: Turbines
Session Chair: Ian Jennions–Cranfield University
Cripple Creek B
  Enhancing Turbine Performance Degradation Prediction with Atmospheric Factors
Xiaomo Jiang1, TsungPo Lin2, Eduardo Mendoza3
1 General Electric Company, Power Services, Monitoring and Diagnostics, Atlanta, GA 30339, USA
2,3 General Electric Company, Power Services, Performance, Atlanta, GA 30339, USA
 
  Gas Turbine Engine Health Data Analysis for Parameter Reduction and Condition Assessment
Amar Kumar1, Alka Srivastava2, Nita Goel3, Marzia Zaman4
1,2,3,4 Tecsis Corporation, 201-203 Colonnade Road, Ottawa, ON, K2E 7J5
  Method and System for Predicting Hydraulic Valve Degradation on a Gas Turbine
James D’Amato1, John Patanian2
1,2 GE Power, Atlanta, GA, 30339, USA
8:45–10:15 Panel Session 2: Wind Energy Crestone A
8:45–10:15 Technology Demonstration: Smartphone Based Multi-Modal Sensor Fusion for PHM [UTRC] Aspen AB
10:15–10:30 Break 3rd Floor Foyer
10:30–12:00 Data Challenge winners Cripple Creek A
10:30–12:00 Session 4B: Diagnostics II
Session Chair: Scott Clements–Lockheed Martin Aeronautics
Cripple Creek B
  A Computationally-Efficient Inverse Approach to Probabilistic Strain-Based Damage Diagnosis
James E. Warner1, Jacob D. Hochhalter2, William P. Leser3, Patrick E. Leser4, John A. Newman5
1,2,3,4,5 NASA Langley Research Center, Hampton, VA, 23666, USA
 
  Reducing Tachometer Jitter to Improve Gear Fault Detection
Eric Bechhoefer1, Dave He2
1 GPMS Inc., Cornwall, VT, 05753, USA
2 Dept. of Mechanical and Industrial Engineering, UIC, Chicago, IL, 6-612, USA
  Distributed Adaptive Fault-Tolerant Formation Control of Second-Order Multi-Agent Systems with Actuator Faults
Mohsen Khalili1, Xiaodong Zhang2, Yongcan Cao3
1,2 Department of Electrical Engineering, Wright State University, Dayton, OH 45435, USA
3 Department of Electrical and Computer Engineering, University of Texas, San Antonio, TX 78249, USA
10:30–12:00 Panel Session 3: Oil and Gas, Automation and PHM Crestone A
10:30–12:00 Technology Demonstration: Machine Learning for Monitoring System Health [MathWorks] Aspen AB
12:00–13:15 Symposium Lunch and Keynote Speech – Rhonda Whalthall, United Technologies Aerospace Systems Crystal Ballroom
13:15–15:00 Session 5A: Industrial & Manufacturing Applications I
Session Chair: Douglas L. Van Bossuyt–Colorado School of Mines
Cripple Creek A
  Inertial Measurement Unit for On-Machine Diagnostics of Machine Tool Linear Axes
Gregory W. Vogl1, M. Alkan Donmez2, Andreas Archenti3, Brian A. Weiss4
1,2,4 National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, 20899, USA
3 KTH Royal Institute of Technology, Brinellvägen 68, 10044, Stockholm, Sweden
 
  Condition Based Monitoring for a Hydraulic Actuator
Stephen Adams1, Peter A. Beling2, Kevin Farinholt3, Nathan Brown4, Sherwood Polter5, Qing Dong6
1,2 University of Virginia, Charlottesville, VA, 22904, USA
3,4 Luna Innovations Inc., Charlottesville, VA, 22903, USA
5,6 Naval Surface Warfare Center Philadelphia Division, Philadelphia, PA
  Present Status and Future Growth of Advanced Maintenance Technology
and Strategy in US Manufacturing

Xiaoning Jin1, Brian Weiss2, David Siegel3, Jay Lee4
1 Department of Mechanical and Industrial Engineering, Northeastern University, MA, 02115, USA
2 National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
3,4 Department of Mechanical & Materials Engineering, University of Cincinnati, USA
13:15–15:00 Session 5B: Features II
Session Chair: Jeff Bird–TECnos
Cripple Creek B
  Time Domain Reflectometry (TDR) Sensor Measurement in Contaminated Oils
Jonathan Geisheimer1, Shilpa Jagannath2, Farhana Zaman3
1,2,3 Meggitt Sensing Systems, Irvine, CA, 92606, USA
 
  Evaluation of Features with Changing Effectiveness for Prognostics
Vepa Atamuradov1, Fatih Camci2
1 Mevlana University Konya Turkey
2 Antalya International University Antalya Turkey
  A Qualitative Fault Isolation Approach for Parametric and Discrete Faults Using Structural Model Decomposition
Matthew Daigle1, Anibal Bregon2, Indranil Roychoudhury3
1 NASA Ames Research Center, Moffett Field, California, 94035, USA
2 Department of Computer Science, University of Valladolid, Valladolid, Spain
3 Stinger Ghaffarian Technologies Inc., NASA Ames Research Center, Moffett Field, California, 94035, USA
13:15–15:00 Panel Session 4: Automotive PHM & Advanced Analytics Crestone A
13:15–15:00 Technology Demonstration: Rapid Oil Debris Identification via ChipCHECK [GasTOPS] Aspen AB
15:00–15:30 Break 3rd Floor Foyer
15:30–17:15 Session 6A: Aviation II
Session Chair: Giovanni Jacazio–Polytechnic University of Turin
Cripple Creek A
  An Application of Data Driven Anomaly Identification to Spacecraft Telemetry Data
Gautam Biswas1, Hamed Khorasgani2, Gerald Stanje3, Abhishek Dubey4, Somnath Deb5, Sudipto Ghoshal6
1,2,3,4 Inst. of Software-integrated Systems, Vanderbilt Univ., USA
5,6 Qualtech Systems, Inc. (QSI), USA
 
  System-level Prognostics for the National Airspace
Matthew Daigle1, Shankar Sankararaman2, Indranil Roychoudhury3
1 NASA Ames Research Center, Moffett Field, CA 94035, USA
2,3 SGT, Inc., NASA Ames Research Center, Moffett Field, CA 94035, USA
  Prognostic Reasoner based Adaptive Power Management System for a More Electric Aircraft
Robin K. Sebastian1, Suresh Peripinayagam2, Ian K. Jennions3, Alireza Alghassi4
1 Hindustan Aeronautics Limited, Aircraft Research and Design Center, Bangalore, Karnataka, 560037, India
2,3,4 IVHM Centre, Cranfield University, Bedfordshire, Bedford, MK43 0AP, UK
15:30–17:15 Session 6B: Batteries I
Session Chair: Amir Kashani–University of Maryland
Cripple Creek B
  Particle-Filtering-Based State-of-Health Estimation and End-of-Life Prognosis for Lithium-Ion Batteries at Operation Temperature
Daniel Pola1, Felipe Guajardo2, Esteban Jofré3, Vanessa Quintero4, Aramis Pérez5, David Acuña6, Marcos Orchard7
1,2,3,4,5,6,7 Department of Electrical Engineering, Faculty of Physical and Mathematical Sciences, Universidad de Chile, Santiago, Chile
 
  Remaining Useful Life Predictions in Lithium-ion Battery under Composite Condition
Yejin Kim1, Jongsoo Lee2
1,2 School of Mechanical Engineering, Yonsei University, Seoul, 120-749, Korea
  Used Lubricating Oil Filter Debris Analysis (FDA) for Problem Diagnostic of Oil Lubricated Machinery
Surapol Raadnui1
1 Department of Production Engineering, King Mongkut’s University of Technology North Bangkok (KMUTNB), 1518, Pracharaj 1 Road, Bang-Sue, District, Bangkok, Postal Code 10800, Bangkok, Thailand, Email address:
15:30–17:15 Panel Session 5: PHM Education and Professional Development Crestone A
15:30–17:15 Technology Demonstration: Smartphone Based Multi-Modal Sensor Fusion for PHM [UTRC] Aspen AB
17:15–19:30 Poster Reception Crystal Ballroom
Wednesday, October 5, 2016 Location
7:00–17:00 Registration 3rd Floor Foyer
7:45–8:00 Continental Breakfast 3rd Floor Foyer
8:00–8:45 Opening Remarks Crystal Ballroom
8:00–8:45 Luminary Presentation: Dr. Daniel Mack, Kansas City Royals Crystal Ballroom
8:45–10:15 Session 7A: Deep Learning I
Session Chair: Steven Adams –University of Virginia
Cripple Creek A
  Deep Learning Based Diagnostics of Orbit Patterns in Rotating Machinery
Haedong Jeong1, Sunhee Woo2, Suhyun Kim3, Seungtae Park4, Heechang Kim5, Seungchul Lee6
1,2,3,4,5,6 Ulsan National Institute of Science and Technology, Ulsan, Korea
 
  Using Deep Learning Based Approaches for Bearing Fault Diagnosis with AE Sensors
Miao He1, David He2, Eric Bechhoefer3
1,2 Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, U.S
3 Green Power Monitoring Systems, Cornwall, VT, 05753, U.S
  Combining Deep Learning and Survival Analysis for Asset Health Management
Linxia Liao1, Hyung-il Ahn2
1 GE Digital, San Ramon, CA, 94583, USA
2 Noodle Analytics, Inc., San Francisco, CA, 94105, USA
8:45–10:15 Session 7B: Systems II
Session Chair: Carl Byington–Sikorsky
Cripple Creek B
  Case Study in Improving the Health of a Remote Monitoring & Diagnostics Center
Sanjeev Heda1
1 General Electric Power Services Engineering, Atlanta, GA 30339
 
  Critical Components Selection for a Prognostics and Health Management System Design: an Application to an Overhead Contact System
Mehdi Brahimi1, Kamal Medjaher2, Mohammed Leouatni3, Noureddine Zerhouni4
1,4 FEMTO-ST Institute, AS2M Department, 25000 Besançon, France
1 ALSTOM, 48 rue Albert Dhalenne, 93400 Saint-Ouen, France
2 Production Engineering Laboratory (LGP), INP-ENIT, 47 Av. d’Azereix, 65000 Tarbes, France
  Engine Health Management in Safran Aircraft Engines
Guillaume Bastard1, Jérome Lacaille2, Josselin Coupard3, Yacine Stouky4
1,2,3,4 Safran Aircraft Engines, Réau, 77550 Moissy-Cramayel, France
8:45–10:15 Panel Session 6: PHM Standards Experience for Manufacturing Crestone A
8:45–10:15 Technology Demonstration: PHM for Static Components [Metis/UTAS] Aspen AB
10:15–10:30 Break 3rd Floor Foyer
10:30–12:00 Session 8A: Data Driven Methods
Session Chair: Jon Bednar–Boeing
Cripple Creek A
  A Data-Driven Health Management Application for Failure Detection and Diagnosis in Electrical Submersible Pumps
Supriya Gupta1, Michael Nikolaou2, Luigi Saputelli3
1,2 University of Houston, Houston, Houston, Texas, 77204-4004
3 Frontender Corporation, Houston, Texas, 77024
 
  Reciprocating compressor valve condition monitoring using image-based pattern recognition
John N. Trout1, Jason R. Kolodziej2
1,2 Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York, 14623, USA
  Comparison of Model-based Vs. Data-driven Methods for Fault Detection and Isolation in Engine Idle Speed Control System
Ruochen Yang1, Giorgio Rizzoni2
1,2 Center for Automotive Research, Columbus, Ohio, 43212, USA
1,2 Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio, 43212, USA
2 Mechanical and Aerospace Engineering, The Ohio State University, Columbus, Ohio, 43212, USA
10:30–12:00 Session 8B: Prognostics II
Session Chair: Ash Thacker–Global Technology Connection
Cripple Creek B
  Deriving Prognostic Continuous Time Bayesian Networks from Fault Trees
Logan Perreault1, Monica Thornton2, John W. Sheppard3
1,2,3 Montana State University, Bozeman, MT, 59717, United States
 
  Probabilistic Prognosis of Non-Planar Fatigue Crack Growth
Patrick E. Leser1, John A. Newman2, James E. Warner3, William P. Leser4, Jacob D. Hochhalter5, Fuh-Gwo Yuan6
1,2,3,4,5 NASA Langley Research Center, Hampton, VA, 23681, USA
6 North Carolina State University, Raleigh, NC, 27695, USA
  A Modelling Ecosystem for Prognostics
Lachlan Astfalck1, Melinda Hodkiewicz2, Adrian Keating3, Edward Cripps4, Michael Pecht5
1,2,3 System Health Laboratory, The University of Western Australia, Perth, WA, 6009, Australia
4 School of Mathematics and Statistics, The University of Western Australia, Perth, WA, 6009, Australia
5 Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD, 20742, USA
10:30–12:00 Panel Session 7: Smart Manufacturing PHM Crestone A
10:30–12:00 Technology Demonstration: Machine Learning for Monitoring System Health [MathWorks] Aspen AB
12:00–13:15 Lunch on your own
13:15–15:00 Session 9A: Missing Data
Session Chair: Peter Beling –University of Virginia
Cripple Creek A
  Application of Multiple-imputation-particle-filter for Parameter Estimation of Visual Binary Stars with Incomplete Observations
Rubén M. Clavería1, David Acuña2, René A. Méndez3, Jorge F. Silva4, Marcos E. Orchard5
1,2,4,5 Universidad de Chile, Department of Electrical Engineering. Av. Tupper 2007, Santiago, Chile
3 Universidad de Chile, Department of Astronomy. Casilla 36-D, Santiago, Chile
 
  Failure Prognostics with Missing Data Using Extended Kalman Filter
Wlamir Olivares Loesch Vianna1, Takashi Yoneyama2
1 EMBRAER S.A., S˜ao José dos Campos, S˜ao Paulo, 12227–901, Brazil
2 ITA – Instituto Tecnológico de Aeronáutica, S˜ao José dos Campos, S˜ao Paulo, 12228-900, Brazil
  On the Practical Performance of Minimal Hitting Set Algorithms from a Diagnostic Perspective
Ingo Pill1, Thomas Quaritsch2, Franz Wotawa3
1,3 Institute for Software Technology, Graz University of Technology, Inffeldgasse 16b/II, 8010 Graz, Austria
2 HTL Pinkafeld, Meierhofplatz 1, 7423 Pinkafeld, Austria
13:15–15:00 Panel Session 8: Railway PHM Cripple Creek B
13:15–15:00 Panel Session 9: Department of Defense (DoD) Condition Based Mainte- nance Plus (CBM+) Service Panel Review Crestone A
13:15–15:00 Technology Demonstration: Rapid Oil Debris Identification via ChipCHECK [GasTOPS] Aspen AB
15:00–15:30 Break 3rd Floor Foyer
15:30–17:15 Session 10A: Deep Learning II
Session Chair: Scott Clements –Lockheed Martin Aeronautics
Cripple Creek A
  Deep Health Indicator Extraction: A Method based on Auto-encoders and Extreme Learning Machines
Yang Hu1, Thomas Palmé2, Olga Fink3
1,3 Zurich University of Applied Sciences, Rosenstr. 3, Winterthur, 8401, Switzerland
2 General Electric (GE) Switzerland, Brown Boveri Str. 7, Baden, 5401, Switzerland
 
  Using Deep Learning Based Approaches for Bearing Remaining Useful Life Prediction
Jason Deutsch1, David He2
1,2 Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, Illinois, 60607, USA
  Deep Learning for Structural Health Monitoring: A Damage Characterization Application
Soumalya Sarkar1, Kishore K. Reddy2, Michael Giering3, Mark R. Gurvich4
1,2,3,4 United Technologies Research Center (UTRC), East Hartford, CT, USA
15:30–17:15 Session 10B: Industrial & Manufacturing Applications II
Session Chair: Brian Weiss–National Institute of Standards
Cripple Creek B
  Case Study of a Faulted Planet Bearing
Eric Bechhoefer1, Dave He2
1 GPMS Inc., Cornwall, VT, 05753, USA
2 Dept. of Mechanical and Industrial Engineering, UIC, Chicago, IL, 6-612, USA
 
  Towards Detection Of Water Management Faults For Pem Fuel Cells Under Variable Load
Pavle Boškoski1, Andrej Debenjak2, Ðani Juričić3, Biljana Mileva Boshkoska4
1,2,3 Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia
4 Faculty of Information Studies in Novo mesto, Ljubljanska cesta 31A, SI-8000 Novo mesto, Slovenia
  Hidden Markov Model-Based Detection and Classification of Foreign Objects in Heat-Exchanger Tubes
Portia Banerjee1, Lalita Udpa2, Satish Udpa3
1,2,3 Michigan State University, East Lansing, MI, 48823, USA
15:30–17:15 Panel Session 10: Select Military Maintenance Projects Funded through the Commercial Technologies for Maintenance Activi- ties (CTMA) Program Crestone A
15:30–17:15 Technology Demonstration: PHM for Static Components [Metis/UTAS] Aspen AB
17:15–17:30 Free Time
17:30–18:00 Buses to Banquet
18:00–21:30 PHM Conference Banquet For guest tickets, please Sports Authority at Mile High Stadium
21:30–22:00 Busses Return to Hotel
Thursday, October 6, 2016 Location
7:00–12:00 Registration 3rd Floor Foyer
7:45–8:00 Continental Breakfast 3rd Floor Foyer
8:00–8:45 Opening Remarks Crystal Ballroom
8:00–8:45 Luminary Presentation: Joint PHM/DX Keynote Presentation: Dr. Rui Abreu, PARC Crystal Ballroom
8:45–10:15 Session 11A: Structural Health Management
Session Chair: Abbas Chokor –Arizona State University
Cripple Creek A
  Detection of Cracks in Shafts via Analysis of Vibrations and Orbital Paths
R. Peretz1, L. Rogel2, J. Bortman3, R. Klein4
1,2,3 Pearlstone Center for Aeronautical Engineering Studies and Laboratory for Mechanical Health Monitoring, Department of Mechanical
4 R.K. Diagnostics, P.O. Box 101, Gilon, D.N. Misgav 20103, Israel
 
  Big Data Analytics in Online Structural Health Monitoring
Guowei Cai1, Sankaran Mahadevan2
1,2 Vanderbilt University, Nashville, TN, 37235, United States
  Quadrotor Actuator Fault Diagnosis with Real-Time Experimental Results
Remus C Avram1, Xiaodong Zhang2, Mohsen Khalili3
1,2,3 Wright State University, Dayton, Ohio, 45404, USA
8:45–10:15 Session 11B: Batteries II
Session Chair:Brinda Thomas–Tesla
Cripple Creek B
  Parameters Optimization of Lebesgue Sampling-based Fault Diagnosis and Prognosis with Application to Li-ion Batteries
Wuzhao Yan1, Bin Zhang2, Marcos Orchard3
1,2 Department of Electrical Engineering
3 Department of Electrical Engineering
 
  A Fusion Method Based on Unscented Particle Filter and Minimum Sampling Variance Resampling for Lithium-ion Battery Remaining Useful Life Prediction
Jiayu Chen1, Dong Zhou2, Chuan Lu3
1 School of Reliability and Systems Engineering, Beihang University, Beijing, 100191, China
2,3 Science and Technology on Reliability and Environmental Engineering Laboratory & State Key Laboratory of Virtual
  Data-Driven Prognostics of Lithium-Ion Rechargeable Battery using Bilinear Kernel Regression
Charlie Hubbard1, John Bavlsik2, Chinmay Hegde3, Chao Hu4
1,3 Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, 50011, USA
2,4 Department of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA
8:45–10:15 Panel Session 11: Big Data Crestone A
10:15–10:30 Break 3rd Floor Foyer
10:30–12:00 Session 12A: PHM for Electrical Systems
Session Chair: José Celaya –Schlumberger
Cripple Creek A
  A Review of Photovoltaic DC Systems Prognostics and Health Management: Challenges and Opportunities
Abbas Chokor1, Mounir El Asmar2, Sumanth V. Lokanath3
1,2 School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, 85281, USA
3 Systems Reliability Engineering Group, First Solar Inc, Mesa, AZ, 85212, USA
 
  Failure Precursor Identification and Degradation Modeling for Insulated Gate Bipolar Transistors Subjected to Electrical Stress
Junmin Lee1, Hyunseok Oh2, Chan Hee Park3, Byeng D. Youn4, Deog Hyeon Kim5, Byung Hwa Kim6, Yong Un Cho7
1,2,3,4 Department of Mechanical Engineering, Seoul National University, Seoul, 08826, Republic of, Korea
5,6,7 Equipment Control Engineering Team 1, Production and Development Division, Hyundai Motor Group, Ulsan, Republic
  Impedance-based Health Monitoring of Electromagnetic Coil Insulation Subjected to Corrosive Deterioration
N. Jordan Jameson1, Michael H. Azarian2, Michael Pecht3
1,2,3 Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD, 20742, USA
10:30–12:00 Session 12B: Deep Learning III
Session Chair: David Siegel –Predictronics
Cripple Creek B
  Wearable EEG-based Activity Recognition in PHM-related Service Environment via Deep Learning
Soumalya Sarkar1, Kishore K. Reddy2, Alex Dorgan3, Cali Fidopiastis4, Michael Giering5
1,2,3,4,5 United Technologies Research Center, East Hartford, CT 06118, USA
 
  Smart Diagnosis of Journal Bearing Rotor Systems: Unsupervised Feature Extraction Scheme by Deep Learning
Hyunseok Oh1, Byung Chul Jeon2, Joon Ha Jung3, Byeng D. Youn4
1,2,3,4 Department of Mechanical Engineering, Seoul National University
  Prognostics of Combustion Instabilities from Hi-speed Flame Video using a Deep Convolutional Selective Autoencoder
Adedotun Akintayo1, Kin Gwn Lore2, Soumalya Sarkar3, Soumik Sarkar4
1,2,4 Mechanical Engineering Department, Iowa State University, Ames, Iowa, 50011, USA
3 Decision Support and Machine Intelligence, United Technologies Research Center, East Hartford, Connecticut, 06118, USA
10:30–12:00 PHM2017 Planning Session Crestone A
12:00–13:15 Lunch on your own
13:15–15:00 Panel Session 12: Fielded Systems Crestone A
15:00–15:30 Closing Remarks Crestone A

Last modified: 26-Sep-2016 16:48:58