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 |
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| 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 |
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| 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 |
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| 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 |
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| 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: |
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| Integration of Failure Assessments into the Diagnostic Process Roxane Koitz1, Franz Wotawa2– 1,2 Institute for Software Technology, Graz, Styria, 8010, Austria |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| PHM Decision Support under Uncertainty Murat Yasar1, Teems E. Lovett2– 1,2 United Technologies Research Center, East Hartford, CT, 06118, USA |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| Evaluation of Features with Changing Effectiveness for Prognostics Vepa Atamuradov1, Fatih Camci2– 1 Mevlana University Konya Turkey 2 Antalya International University Antalya Turkey |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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: |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| Big Data Analytics in Online Structural Health Monitoring Guowei Cai1, Sankaran Mahadevan2– 1,2 Vanderbilt University, Nashville, TN, 37235, United States |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |