1. @ Technology & Innovation Centre, University of Strathclyde
Space Robotics Symposium 2015
An Integrated Framework for Intelligent Reliability Design and Prognostic Health Management of
Space Robotic System
Prof. Zhonglai Wang
University of Electronic Science and Technology of China
Dr. Yi Chen
Glasgow Caledonian University
Dr. Erfu Yang
University of Strathclyde
@ Technology & Innovation Centre, University of Strathclyde
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2. OUTLINE Motivation Integrated Framework Case Study Future Work 1 2 3 4
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3. ● Degradation ● Fracture Time-variant failure modes
Motivation
● Vacuum ● Microgravity
● Temperature ● Debris
● Friction ● Shocks
● Degradation ● Fracture
Time-variant failure modes
Harsh Space
Environment
Improve designed reliability
Reliability-based design optimization (RBDO)
Prognostic health management(PHM)
Integrated framework of RBDO and PHM
Improve operating reliability
Improve design and operating reliability
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4. Integrated Framework (iRPHM)
Methodologies and Applications of iRPHM for Space Robotic Systems
Failure Mechanism analysis
Time-variant reliability indexes
PHM framework and analysis
iRPHM framework design
Case study
Dynamic analysis
method under
coupled uncertain
field;
Failure mechanism
analysis method;
PHM framework
Construction;
analysis;
Time-variant reliability
analysis method;
Time-variant model
validation technique;
iRPHM mathematic model;
iRPHM design;
Application;
Methodology validation.
Validation and Improvement of Proposed Methodologies
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6. Failure mechanism analysis
Coupled space conditions analysis
Dynamic analysis
Failure mechanism analysis
► Vacuum
► Microgravity
► Variant temperature
► Micrometeoroid
► Space debris
● Dynamic behaviour
● Failure mechanism
State of the Art: MORE literatures on single input but LESS on multiple inputs.
Novelties: Add new ports by improving the bond graph for more inputs;
evolution procedure of failure mechanism.
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7. Time-variant reliability analysis
Space environment
Strength degradation
Mechanism motion
Time-variant
Correlated failure modes
State of the Art: Time-invariant correlation MORE, time-variant LESS.
Novelties: Time-variant Copula function for improving computational accuracy.
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8. Time-variant reliability model validation
Monitoring data
Field data
Experimental data
Time-variant
State of the Art: Time-invariant and sample invariant MORE, consider time and sample LESS.
Novelties: Time-variant B-distance validation index covers time and samples.
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9. PHM framework and analysis
State of the Art: The construction of PHM framework at the early stage; MORE data-driven prognosis, LESS failure mechanism driven prognosis.
Novelties: From the aspect of lifecycle, study the PHM framework; Dynamic prognosis based on failure mechanism.
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10. iRPHM design
Mathematic model construction and design
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11. Computation Intelligence (CI)-aided design for iRPHM
CI Aided Design (CIAD) for iRPHM
CI integrated solver
Y. Chen, SwarmWolf - The Artificial Wolf Pack Algorithm (AWPA),
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12. Case study Random variables 4 design variables and 21 constraints
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13. Considering strength degradation
Case study
Considering strength degradation
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14. Concurrent design optimization
Case study
Concurrent design optimization
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15. Case study
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16. Future Works IRPHM software platform development and testing
System integration and validation
Application explorations for more space robotic systems, e.g.:
robotic space tether
space exoskeleton
Orbital-servicing manipulators
Planetary rovers,etc

17. Q&A
Thanks!
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